Delete Last Commit.txt

Last Commit.txt

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-import spaces
-import gradio as gr
-import torch
-from PIL import Image
-from diffusers import DiffusionPipeline
-import random
-import uuid
-from typing import Tuple
-import numpy as np
-
-DESCRIPTIONz = """## FLUX REALISM 🔥"""
-
-
-DESCRIPTIONy = """
-            <p align="left">
-            <a title="Github" href="https://github.com/PRITHIVSAKTHIUR/FLUX-REALPIX" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
-                <img src="https://img.shields.io/github/stars/PRITHIVSAKTHIUR/FLUX-REALPIX?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="badge-github-stars">
-            </a>
-            </p>
-"""
-
-def save_image(img):
-    unique_name = str(uuid.uuid4()) + ".png"
-    img.save(unique_name)
-    return unique_name
-
-def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    return seed
-
-MAX_SEED = np.iinfo(np.int32).max
-
-if not torch.cuda.is_available():
-    DESCRIPTIONz += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
-
-base_model = "black-forest-labs/FLUX.1-dev"
-pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
-
-lora_repo = "prithivMLmods/Canopus-LoRA-Flux-FaceRealism"
-trigger_word = "Realism"  # Leave trigger_word blank if not used.
-pipe.load_lora_weights(lora_repo)
-
-pipe.to("cuda")
-
-style_list = [
-    {
-        "name": "3840 x 2160",
-        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-    },
-    {
-        "name": "2560 x 1440",
-        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-    },
-    {
-        "name": "HD+",
-        "prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-    },
-    {
-        "name": "Style Zero",
-        "prompt": "{prompt}",
-    },
-]
-
-styles = {k["name"]: k["prompt"] for k in style_list}
-
-DEFAULT_STYLE_NAME = "3840 x 2160"
-STYLE_NAMES = list(styles.keys())
-
-def apply_style(style_name: str, positive: str) -> str:
-    return styles.get(style_name, styles[DEFAULT_STYLE_NAME]).replace("{prompt}", positive)
-
-@spaces.GPU(duration=60, enable_queue=True)
-def generate(
-    prompt: str,
-    seed: int = 0,
-    width: int = 1024,
-    height: int = 1024,
-    guidance_scale: float = 3,
-    randomize_seed: bool = False,
-    style_name: str = DEFAULT_STYLE_NAME,
-    progress=gr.Progress(track_tqdm=True),
-):
-    seed = int(randomize_seed_fn(seed, randomize_seed))
-
-    positive_prompt = apply_style(style_name, prompt)
-    
-    if trigger_word:
-        positive_prompt = f"{trigger_word} {positive_prompt}"
-
-    images = pipe(
-        prompt=positive_prompt,
-        width=width,
-        height=height,
-        guidance_scale=guidance_scale,
-        num_inference_steps=16,
-        num_images_per_prompt=1,
-        output_type="pil",
-    ).images
-    image_paths = [save_image(img) for img in images]
-    print(image_paths)
-    return image_paths, seed
-
-
-def load_predefined_images():
-    predefined_images = [
-        "assets/11.png",
-        "assets/22.png",
-        "assets/33.png",
-        "assets/44.png",
-        "assets/55.webp",
-        "assets/66.png",
-        "assets/77.png",
-        "assets/88.png",
-        "assets/99.png",
-    ]
-    return predefined_images
-
-
-
-examples = [
-    "A portrait of an attractive woman in her late twenties with light brown hair and purple, wearing large a a yellow sweater. She is looking directly at the camera, standing outdoors near trees.. --ar 128:85 --v 6.0 --style raw",
-    "A photo of the model wearing a white bodysuit and beige trench coat, posing in front of a train station with hands on head, soft light, sunset, fashion photography, high resolution, 35mm lens, f/22, natural lighting, global illumination. --ar 85:128 --v 6.0 --style raw",
-]
-
-
-css = '''
-.gradio-container{max-width: 575px !important}
-h1{text-align:center}
-footer {
-    visibility: hidden
-}
-'''
-
-with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    gr.Markdown(DESCRIPTIONz)
-    gr.Markdown(DESCRIPTIONy)
-    with gr.Row():
-        prompt = gr.Text(
-            label="Prompt",
-            show_label=False,
-            max_lines=1,
-            placeholder="Enter your prompt",
-            container=False,
-        )
-        run_button = gr.Button("Run", scale=0)
-    result = gr.Gallery(label="Result", columns=1, show_label=False) 
-    
-    with gr.Accordion("Advanced options", open=False, visible=True):
-        seed = gr.Slider(
-            label="Seed",
-            minimum=0,
-            maximum=MAX_SEED,
-            step=1,
-            value=0,
-            visible=True
-        )
-        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-        
-        with gr.Row(visible=True):
-            width = gr.Slider(
-                label="Width",
-                minimum=512,
-                maximum=2048,
-                step=64,
-                value=1024,
-            )
-            height = gr.Slider(
-                label="Height",
-                minimum=512,
-                maximum=2048,
-                step=64,
-                value=1024,
-            )
-        
-        with gr.Row():
-            guidance_scale = gr.Slider(
-                label="Guidance Scale",
-                minimum=0.1,
-                maximum=20.0,
-                step=0.1,
-                value=3.0,
-            )
-            num_inference_steps = gr.Slider(
-                label="Number of inference steps",
-                minimum=1,
-                maximum=40,
-                step=1,
-                value=16,
-            )
-
-        style_selection = gr.Radio(
-            show_label=True,
-            container=True,
-            interactive=True,
-            choices=STYLE_NAMES,
-            value=DEFAULT_STYLE_NAME,
-            label="Quality Style",
-        )
-
-
-
-    gr.Examples(
-        examples=examples,
-        inputs=prompt,
-        outputs=[result, seed],
-        fn=generate,
-        cache_examples=False,
-    )
-
-    gr.on(
-        triggers=[
-            prompt.submit,
-            run_button.click,
-        ],
-        fn=generate,
-        inputs=[
-            prompt,
-            seed,
-            width,
-            height,
-            guidance_scale,
-            randomize_seed,
-            style_selection,
-        ],
-        outputs=[result, seed],
-        api_name="run",
-    )
-    
-    gr.Markdown("### Generated Images")
-    predefined_gallery = gr.Gallery(label="Generated Images", columns=3, show_label=False, value=load_predefined_images())
-
-
-    gr.Markdown("**Disclaimer/Note:**")
-    
-    gr.Markdown("🔥This space provides realistic image generation, which works better for human faces and portraits. Realistic trigger works properly, better for photorealistic trigger words, close-up shots, face diffusion, male, female characters.")
-   
-    gr.Markdown("🔥users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards.")
-    
-if __name__ == "__main__":
-    demo.queue(max_size=40).launch()