Uploaded Necessary Files

app.py

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+import torch
+from transformers import (
+    AutoModelForCausalLM,
+    AutoTokenizer,
+    CLIPVisionModel,
+    CLIPImageProcessor
+)
+from peft import PeftModel
+import gradio as gr
+from PIL import Image
+import os
+from prompt_templates import PROMPT_TEMPLATES, RESPONSE_TEMPLATES, ANALYSIS_TEMPLATES
+import numpy as np
+import cv2
+
+class VLMInference:
+    def __init__(self):
+        # Initialize vision model
+        self.vision_model = CLIPVisionModel.from_pretrained(
+            "openai/clip-vit-base-patch32",
+            device_map="auto",
+            torch_dtype=torch.float16
+        )
+        self.image_processor = CLIPImageProcessor.from_pretrained("openai/clip-vit-base-patch32")
+        
+        # Initialize language model
+        self.language_model = AutoModelForCausalLM.from_pretrained(
+            "microsoft/phi-2",
+            device_map="auto",
+            torch_dtype=torch.float16,
+            trust_remote_code=True
+        )
+        
+        # Find the most recent trained model
+        model_dirs = [d for d in os.listdir(".") if d.startswith("best_vlm_model")]
+        if model_dirs:
+            # Sort directories by timestamp if available, otherwise by name
+            def get_timestamp(d):
+                try:
+                    return int(d.split("_")[-1])
+                except ValueError:
+                    return 0  # For directories without timestamps
+            
+            latest_model = sorted(model_dirs, key=get_timestamp)[-1]
+            model_path = latest_model
+            print(f"Loading trained model from: {model_path}")
+            
+            # Load the trained LoRA weights
+            self.language_model = PeftModel.from_pretrained(
+                self.language_model,
+                model_path
+            )
+            print("Successfully loaded trained LoRA weights")
+        else:
+            print("No trained model found. Using base model.")
+        
+        # Initialize tokenizer
+        self.tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2")
+        self.tokenizer.pad_token = self.tokenizer.eos_token
+        
+        # Projection layer
+        self.projection = torch.nn.Linear(
+            self.vision_model.config.hidden_size,
+            self.language_model.config.hidden_size
+        ).half()
+        
+        # Move to GPU if available
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.vision_model.to(self.device)
+        self.language_model.to(self.device)
+        self.projection.to(self.device)
+        
+    def analyze_image(self, image):
+        # Convert PIL Image to numpy array
+        if isinstance(image, torch.Tensor):
+            # If image is a tensor, move to CPU and convert to numpy
+            img_np = image.cpu().numpy().transpose(1, 2, 0)
+            # Denormalize if needed (assuming image was normalized)
+            img_np = (img_np * 255).astype(np.uint8)
+        else:
+            # If image is PIL Image, convert directly
+            img_np = np.array(image)
+        
+        # Basic color statistics
+        r, g, b = np.mean(img_np, axis=(0,1))
+        r_std, g_std, b_std = np.std(img_np, axis=(0,1))
+        
+        # Convert to grayscale for brightness and edge analysis
+        gray = cv2.cvtColor(img_np, cv2.COLOR_RGB2GRAY)
+        brightness = np.mean(gray)
+        contrast = np.std(gray)
+        
+        # Edge detection
+        edges = cv2.Canny(gray, 100, 200)
+        edge_density = np.sum(edges > 0) / (edges.shape[0] * edges.shape[1]) * 100
+        
+        # Regional brightness analysis
+        h, w = gray.shape
+        top = np.mean(gray[:h//2, :])
+        bottom = np.mean(gray[h//2:, :])
+        left = np.mean(gray[:, :w//2])
+        right = np.mean(gray[:, w//2:])
+        
+        return {
+            "color": ANALYSIS_TEMPLATES["color"].format(
+                r=int(r), g=int(g), b=int(b),
+                r_std=int(r_std), g_std=int(g_std), b_std=int(b_std)
+            ),
+            "brightness": ANALYSIS_TEMPLATES["brightness"].format(
+                brightness=int(brightness),
+                contrast=int(contrast)
+            ),
+            "edges": ANALYSIS_TEMPLATES["edges"].format(
+                edge_density=int(edge_density)
+            ),
+            "regions": ANALYSIS_TEMPLATES["regions"].format(
+                top=int(top), bottom=int(bottom),
+                left=int(left), right=int(right)
+            )
+        }
+        
+    def process_image(self, image):
+        # Process image
+        image = self.image_processor(image, return_tensors="pt")["pixel_values"][0].to(self.device)
+        
+        # Get vision features
+        with torch.no_grad():
+            vision_outputs = self.vision_model(image.unsqueeze(0))
+            vision_features = vision_outputs.last_hidden_state.mean(dim=1)
+            vision_features = self.projection(vision_features)
+        
+        return vision_features
+    
+    def generate_response(self, image, prompt_type, custom_prompt=None):
+        # Process image
+        image = self.image_processor(image, return_tensors="pt")["pixel_values"][0].to(self.device)
+        
+        # Get vision features
+        with torch.no_grad():
+            vision_outputs = self.vision_model(image.unsqueeze(0))
+            vision_features = vision_outputs.last_hidden_state.mean(dim=1)
+            vision_features = self.projection(vision_features)
+        
+        # Analyze image
+        analysis = self.analyze_image(image)
+        
+        # Format prompt based on type
+        if custom_prompt:
+            prompt = custom_prompt
+        else:
+            prompt = np.random.choice(PROMPT_TEMPLATES[prompt_type])
+        
+        # Format full prompt with analysis
+        full_prompt = f"### Instruction: {prompt}\n\nImage Analysis:\n"
+        for key, value in analysis.items():
+            full_prompt += f"{value}\n"
+        full_prompt += "\n### Response:"
+        
+        # Tokenize
+        inputs = self.tokenizer(
+            full_prompt,
+            return_tensors="pt",
+            padding=True,
+            truncation=True,
+            max_length=512
+        ).to(self.device)
+        
+        # Generate response
+        with torch.no_grad():
+            # Generate using the base model
+            outputs = self.language_model.generate(
+                input_ids=inputs["input_ids"],
+                attention_mask=inputs["attention_mask"],
+                max_length=512,
+                num_return_sequences=1,
+                temperature=0.7,
+                do_sample=True,
+                pad_token_id=self.tokenizer.pad_token_id,
+                eos_token_id=self.tokenizer.eos_token_id
+            )
+        
+        # Decode response
+        response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        response = response.split("### Response:")[1].strip()
+        
+        return response, analysis
+
+def create_interface():
+    # Initialize model
+    model = VLMInference()
+    
+    def process_image_and_prompt(image, prompt_type, custom_prompt):
+        try:
+            response, analysis = model.generate_response(image, prompt_type, custom_prompt)
+            
+            # Format the output
+            output = f"Response:\n{response}\n\nImage Analysis:\n"
+            for key, value in analysis.items():
+                output += f"{value}\n"
+            
+            return output
+        except Exception as e:
+            return f"Error: {str(e)}"
+    
+    # Load sample images from enhanced CIFAR10 dataset
+    sample_images = []
+    sample_labels = []
+    dataset_dir = "enhanced_cifar10_dataset"
+    
+    if os.path.exists(dataset_dir):
+        for filename in os.listdir(dataset_dir):
+            if filename.startswith("enhanced_cifar10_") and filename.endswith(".png"):
+                class_name = filename.replace("enhanced_cifar10_", "").replace(".png", "")
+                image_path = os.path.join(dataset_dir, filename)
+                try:
+                    # Load and verify the image
+                    img = Image.open(image_path)
+                    img.verify()  # Verify it's a valid image
+                    sample_images.append(image_path)
+                    sample_labels.append(class_name)
+                except Exception as e:
+                    print(f"Error loading image {image_path}: {str(e)}")
+    
+    # Create Gradio interface
+    with gr.Blocks(title="Vision-Language Model Demo") as interface:
+        gr.Markdown("# Vision-Language Model Demo")
+        gr.Markdown("Select a sample image from the enhanced CIFAR10 dataset or upload your own image.")
+        
+        with gr.Row():
+            with gr.Column():
+                # Sample images gallery
+                if sample_images:
+                    gr.Markdown("### Sample Images from Enhanced CIFAR10 Dataset")
+                    sample_gallery = gr.Gallery(
+                        value=[(img, label) for img, label in zip(sample_images, sample_labels)],
+                        label="Select a sample image",
+                        columns=5,
+                        height="auto",
+                        object_fit="contain"
+                    )
+                else:
+                    gr.Markdown("No sample images found in the enhanced CIFAR10 dataset.")
+                
+                # Image input
+                image_input = gr.Image(type="pil", label="Upload Image")
+                
+                # Prompt selection
+                prompt_type = gr.Dropdown(
+                    choices=list(PROMPT_TEMPLATES.keys()),
+                    value="basic",
+                    label="Select Prompt Type"
+                )
+                custom_prompt = gr.Textbox(
+                    label="Custom Prompt (optional)",
+                    placeholder="Enter your own prompt here..."
+                )
+                submit_btn = gr.Button("Generate Response")
+            
+            with gr.Column():
+                output_text = gr.Textbox(
+                    label="Model Response and Analysis",
+                    lines=15
+                )
+        
+        # Add click event for sample gallery
+        if sample_images:
+            def load_selected_image(evt: gr.SelectData):
+                if evt.index < len(sample_images):
+                    return Image.open(sample_images[evt.index])
+                return None
+            
+            sample_gallery.select(
+                fn=load_selected_image,
+                inputs=[],
+                outputs=[image_input]
+            )
+        
+        submit_btn.click(
+            fn=process_image_and_prompt,
+            inputs=[image_input, prompt_type, custom_prompt],
+            outputs=[output_text]
+        )
+    
+    return interface
+
+if __name__ == "__main__":
+    interface = create_interface()
+    interface.launch(share=True) 

best_vlm_model_1744099796/README.md

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+---
+base_model: microsoft/phi-2
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.14.0

best_vlm_model_1744099796/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "microsoft/phi-2",
+  "bias": "none",
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "v_proj",
+    "q_proj",
+    "dense"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

best_vlm_model_1744099796/adapter_model.safetensors

@@ -0,0 +1,3 @@
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+oid sha256:6e6849489d64b4b90f1d3dc71d03288f0f113bb56027962550944de9bc58a70b
+size 21005448

enhanced_cifar10_dataset/responses_bird.txt

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+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a bird. It is a clear and detailed view, showing distinctive features typical of a bird.
+
+Prompt: What do you see in this image?
+Response: This image shows a bird. It is a clear and detailed view, showing distinctive features typical of a bird.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a bird. It is a clear and detailed view, showing distinctive features typical of a bird.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a bird. It is a clear and detailed view, showing distinctive features typical of a bird.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a bird. It is a clear and detailed view, showing distinctive features typical of a bird.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a bird. Analysis of its visual properties reveals: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges. Regional brightness varies with top: 181, bottom: 138, left: 125, right: 194.. These characteristics are consistent with typical bird features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this bird?
+Response: Looking at this bird, I can see the following specific details: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges.
+
+Prompt: What specific pose or position is this bird in?
+Response: Looking at this bird, I can see the following specific details: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this bird, I can see the following specific details: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges.
+
+Prompt: How does this bird stand out from its background?
+Response: Looking at this bird, I can see the following specific details: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges.
+
+Prompt: What makes this particular bird unique or interesting?
+Response: Looking at this bird, I can see the following specific details: The image has average RGB values of R:159, G:159, B:159 with variations of �118, �118, �118. The overall brightness is 159/255 with a contrast level of 118. Edge density analysis shows 20% of pixels forming edges.

enhanced_cifar10_dataset/responses_car.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a car. It is a clear and detailed view, showing distinctive features typical of a car.
+
+Prompt: What do you see in this image?
+Response: This image shows a car. It is a clear and detailed view, showing distinctive features typical of a car.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a car. It is a clear and detailed view, showing distinctive features typical of a car.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a car. It is a clear and detailed view, showing distinctive features typical of a car.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a car. It is a clear and detailed view, showing distinctive features typical of a car.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a car. Analysis of its visual properties reveals: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges. Regional brightness varies with top: 183, bottom: 106, left: 132, right: 157.. These characteristics are consistent with typical car features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this car?
+Response: Looking at this car, I can see the following specific details: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges.
+
+Prompt: What specific pose or position is this car in?
+Response: Looking at this car, I can see the following specific details: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this car, I can see the following specific details: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges.
+
+Prompt: How does this car stand out from its background?
+Response: Looking at this car, I can see the following specific details: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges.
+
+Prompt: What makes this particular car unique or interesting?
+Response: Looking at this car, I can see the following specific details: The image has average RGB values of R:142, G:142, B:148 with variations of �116, �116, �114. The overall brightness is 144/255 with a contrast level of 115. Edge density analysis shows 38% of pixels forming edges.

enhanced_cifar10_dataset/responses_cat.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a cat. It is a clear and detailed view, showing distinctive features typical of a cat.
+
+Prompt: What do you see in this image?
+Response: This image shows a cat. It is a clear and detailed view, showing distinctive features typical of a cat.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a cat. It is a clear and detailed view, showing distinctive features typical of a cat.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a cat. It is a clear and detailed view, showing distinctive features typical of a cat.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a cat. It is a clear and detailed view, showing distinctive features typical of a cat.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a cat. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges. Regional brightness varies with top: 176, bottom: 116, left: 124, right: 168.. These characteristics are consistent with typical cat features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this cat?
+Response: Looking at this cat, I can see the following specific details: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges.
+
+Prompt: What specific pose or position is this cat in?
+Response: Looking at this cat, I can see the following specific details: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this cat, I can see the following specific details: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges.
+
+Prompt: How does this cat stand out from its background?
+Response: Looking at this cat, I can see the following specific details: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges.
+
+Prompt: What makes this particular cat unique or interesting?
+Response: Looking at this cat, I can see the following specific details: The image has average RGB values of R:148, G:145, B:144 with variations of �120, �121, �121. The overall brightness is 146/255 with a contrast level of 121. Edge density analysis shows 24% of pixels forming edges.

enhanced_cifar10_dataset/responses_deer.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a deer. It is a clear and detailed view, showing distinctive features typical of a deer.
+
+Prompt: What do you see in this image?
+Response: This image shows a deer. It is a clear and detailed view, showing distinctive features typical of a deer.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a deer. It is a clear and detailed view, showing distinctive features typical of a deer.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a deer. It is a clear and detailed view, showing distinctive features typical of a deer.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a deer. It is a clear and detailed view, showing distinctive features typical of a deer.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a deer. Analysis of its visual properties reveals: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges. Regional brightness varies with top: 204, bottom: 80, left: 124, right: 160.. These characteristics are consistent with typical deer features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this deer?
+Response: Looking at this deer, I can see the following specific details: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges.
+
+Prompt: What specific pose or position is this deer in?
+Response: Looking at this deer, I can see the following specific details: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this deer, I can see the following specific details: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges.
+
+Prompt: How does this deer stand out from its background?
+Response: Looking at this deer, I can see the following specific details: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges.
+
+Prompt: What makes this particular deer unique or interesting?
+Response: Looking at this deer, I can see the following specific details: The image has average RGB values of R:154, G:144, B:129 with variations of �112, �117, �120. The overall brightness is 142/255 with a contrast level of 115. Edge density analysis shows 48% of pixels forming edges.

enhanced_cifar10_dataset/responses_dog.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a dog. It is a clear and detailed view, showing distinctive features typical of a dog.
+
+Prompt: What do you see in this image?
+Response: This image shows a dog. It is a clear and detailed view, showing distinctive features typical of a dog.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a dog. It is a clear and detailed view, showing distinctive features typical of a dog.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a dog. It is a clear and detailed view, showing distinctive features typical of a dog.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a dog. It is a clear and detailed view, showing distinctive features typical of a dog.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a dog. Analysis of its visual properties reveals: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges. Regional brightness varies with top: 83, bottom: 169, left: 156, right: 97.. These characteristics are consistent with typical dog features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this dog?
+Response: Looking at this dog, I can see the following specific details: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges.
+
+Prompt: What specific pose or position is this dog in?
+Response: Looking at this dog, I can see the following specific details: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this dog, I can see the following specific details: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges.
+
+Prompt: How does this dog stand out from its background?
+Response: Looking at this dog, I can see the following specific details: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges.
+
+Prompt: What makes this particular dog unique or interesting?
+Response: Looking at this dog, I can see the following specific details: The image has average RGB values of R:128, G:125, B:125 with variations of �123, �123, �123. The overall brightness is 126/255 with a contrast level of 123. Edge density analysis shows 19% of pixels forming edges.

enhanced_cifar10_dataset/responses_frog.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a frog. It is a clear and detailed view, showing distinctive features typical of a frog.
+
+Prompt: What do you see in this image?
+Response: This image shows a frog. It is a clear and detailed view, showing distinctive features typical of a frog.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a frog. It is a clear and detailed view, showing distinctive features typical of a frog.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a frog. It is a clear and detailed view, showing distinctive features typical of a frog.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a frog. It is a clear and detailed view, showing distinctive features typical of a frog.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a frog. Analysis of its visual properties reveals: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges. Regional brightness varies with top: 137, bottom: 160, left: 132, right: 165.. These characteristics are consistent with typical frog features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this frog?
+Response: Looking at this frog, I can see the following specific details: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges.
+
+Prompt: What specific pose or position is this frog in?
+Response: Looking at this frog, I can see the following specific details: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this frog, I can see the following specific details: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges.
+
+Prompt: How does this frog stand out from its background?
+Response: Looking at this frog, I can see the following specific details: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges.
+
+Prompt: What makes this particular frog unique or interesting?
+Response: Looking at this frog, I can see the following specific details: The image has average RGB values of R:148, G:148, B:148 with variations of �116, �116, �116. The overall brightness is 148/255 with a contrast level of 116. Edge density analysis shows 35% of pixels forming edges.

enhanced_cifar10_dataset/responses_horse.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a horse. It is a clear and detailed view, showing distinctive features typical of a horse.
+
+Prompt: What do you see in this image?
+Response: This image shows a horse. It is a clear and detailed view, showing distinctive features typical of a horse.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a horse. It is a clear and detailed view, showing distinctive features typical of a horse.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a horse. It is a clear and detailed view, showing distinctive features typical of a horse.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a horse. It is a clear and detailed view, showing distinctive features typical of a horse.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a horse. Analysis of its visual properties reveals: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges. Regional brightness varies with top: 173, bottom: 99, left: 128, right: 143.. These characteristics are consistent with typical horse features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this horse?
+Response: Looking at this horse, I can see the following specific details: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges.
+
+Prompt: What specific pose or position is this horse in?
+Response: Looking at this horse, I can see the following specific details: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this horse, I can see the following specific details: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges.
+
+Prompt: How does this horse stand out from its background?
+Response: Looking at this horse, I can see the following specific details: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges.
+
+Prompt: What makes this particular horse unique or interesting?
+Response: Looking at this horse, I can see the following specific details: The image has average RGB values of R:136, G:135, B:136 with variations of �119, �120, �120. The overall brightness is 136/255 with a contrast level of 120. Edge density analysis shows 30% of pixels forming edges.

enhanced_cifar10_dataset/responses_plane.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a plane. It is a clear and detailed view, showing distinctive features typical of a plane.
+
+Prompt: What do you see in this image?
+Response: This image shows a plane. It is a clear and detailed view, showing distinctive features typical of a plane.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a plane. It is a clear and detailed view, showing distinctive features typical of a plane.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a plane. It is a clear and detailed view, showing distinctive features typical of a plane.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a plane. It is a clear and detailed view, showing distinctive features typical of a plane.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a plane. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges. Regional brightness varies with top: 198, bottom: 130, left: 167, right: 162.. These characteristics are consistent with typical plane features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this plane?
+Response: Looking at this plane, I can see the following specific details: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges.
+
+Prompt: What specific pose or position is this plane in?
+Response: Looking at this plane, I can see the following specific details: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this plane, I can see the following specific details: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges.
+
+Prompt: How does this plane stand out from its background?
+Response: Looking at this plane, I can see the following specific details: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges.
+
+Prompt: What makes this particular plane unique or interesting?
+Response: Looking at this plane, I can see the following specific details: The image has average RGB values of R:164, G:164, B:164 with variations of �118, �118, �118. The overall brightness is 164/255 with a contrast level of 118. Edge density analysis shows 15% of pixels forming edges.

enhanced_cifar10_dataset/responses_ship.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a ship. It is a clear and detailed view, showing distinctive features typical of a ship.
+
+Prompt: What do you see in this image?
+Response: This image shows a ship. It is a clear and detailed view, showing distinctive features typical of a ship.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a ship. It is a clear and detailed view, showing distinctive features typical of a ship.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a ship. It is a clear and detailed view, showing distinctive features typical of a ship.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a ship. It is a clear and detailed view, showing distinctive features typical of a ship.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a ship. Analysis of its visual properties reveals: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges. Regional brightness varies with top: 184, bottom: 114, left: 148, right: 150.. These characteristics are consistent with typical ship features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this ship?
+Response: Looking at this ship, I can see the following specific details: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges.
+
+Prompt: What specific pose or position is this ship in?
+Response: Looking at this ship, I can see the following specific details: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this ship, I can see the following specific details: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges.
+
+Prompt: How does this ship stand out from its background?
+Response: Looking at this ship, I can see the following specific details: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges.
+
+Prompt: What makes this particular ship unique or interesting?
+Response: Looking at this ship, I can see the following specific details: The image has average RGB values of R:164, G:141, B:142 with variations of �107, �122, �122. The overall brightness is 149/255 with a contrast level of 115. Edge density analysis shows 39% of pixels forming edges.

enhanced_cifar10_dataset/responses_truck.txt

@@ -0,0 +1,91 @@
+
+=== BASIC PROMPTS ===
+
+Prompt: Describe this image in detail.
+Response: This image shows a truck. It is a clear and detailed view, showing distinctive features typical of a truck.
+
+Prompt: What do you see in this image?
+Response: This image shows a truck. It is a clear and detailed view, showing distinctive features typical of a truck.
+
+Prompt: Analyze the contents of this image.
+Response: This image shows a truck. It is a clear and detailed view, showing distinctive features typical of a truck.
+
+Prompt: Explain what's happening in this image.
+Response: This image shows a truck. It is a clear and detailed view, showing distinctive features typical of a truck.
+
+Prompt: Provide a detailed description of this image.
+Response: This image shows a truck. It is a clear and detailed view, showing distinctive features typical of a truck.
+
+=== ANALYTICAL PROMPTS ===
+
+Prompt: Describe what you see in this image, considering its visual characteristics.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Based on the image analysis, what object or subject is shown?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: How do the color and brightness patterns relate to the content?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Analyze the image features and explain what they reveal about the subject.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Describe how the regional brightness differences inform the image content.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: What patterns or structures can you identify from the edge density?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: How do the dominant colors help identify the subject?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Explain how the brightness distribution relates to the image composition.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+=== TECHNICAL PROMPTS ===
+
+Prompt: Analyze the color distribution and its impact on the image content.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: How do the edge patterns contribute to the object recognition?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Describe the relationship between brightness distribution and subject matter.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: What can you infer from the regional brightness variations?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: How do the dominant colors influence the perception of the subject?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+=== COMPARATIVE PROMPTS ===
+
+Prompt: Compare the visual characteristics of this image with typical examples of its class.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: How does this image's color distribution differ from other images in its category?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: What makes this particular instance unique within its class?
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+Prompt: Analyze how this image's features align with or deviate from its class characteristics.
+Response: The image presents a truck. Analysis of its visual properties reveals: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges. Regional brightness varies with top: 203, bottom: 24, left: 108, right: 118.. These characteristics are consistent with typical truck features.
+
+=== FOCUSED PROMPTS ===
+
+Prompt: What is the exact color and appearance of this truck?
+Response: Looking at this truck, I can see the following specific details: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges.
+
+Prompt: What specific pose or position is this truck in?
+Response: Looking at this truck, I can see the following specific details: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges.
+
+Prompt: What distinguishing features can you see clearly?
+Response: Looking at this truck, I can see the following specific details: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges.
+
+Prompt: How does this truck stand out from its background?
+Response: Looking at this truck, I can see the following specific details: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges.
+
+Prompt: What makes this particular truck unique or interesting?
+Response: Looking at this truck, I can see the following specific details: The image has average RGB values of R:113, G:113, B:113 with variations of �117, �117, �117. The overall brightness is 113/255 with a contrast level of 117. Edge density analysis shows 36% of pixels forming edges.

requirements.txt

@@ -0,0 +1,12 @@
+gradio>=3.50.2
+torch>=2.0.0
+torchvision>=0.15.0
+transformers>=4.30.0
+Pillow>=9.0.0
+accelerate>=0.20.0
+bitsandbytes>=0.40.0
+peft>=0.4.0
+datasets>=2.12.0
+opencv-python>=4.7.0
+numpy>=1.24.0
+tqdm>=4.65.0