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README.md
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# Model Card for Pixelated Captcha Digit Detection
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## Model Details
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- **License:** Apache-2.0
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- **Developed by:** Saidi Souhaieb
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- **Finetuned from model:** YOLOv8
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## Uses
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This model is designed to detect pixelated captcha digits by showing bounding boxes and extracting the coordinates of the detections.
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## How to Get Started with the Model
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```python
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from PIL import Image, ImageDraw
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from YOLO import YOLO # Assuming YOLO is a class in a module named YOLO
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# Load the model
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model = YOLO("models/number_finder.pt")
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# Get model results
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model_results = model(image_path)
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img = Image.open(image_path)
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draw = ImageDraw.Draw(img)
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# Sort results based on the x-coordinate
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detected_objects = []
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captcha_result = ""
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boxes_data = []
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for result in model_results:
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for box in result.boxes:
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box_data = {"xyxy": box.xyxy[0].tolist(),
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"label": str(box.cls.item())}
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boxes_data.append(box_data)
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sorted_boxes_data = sorted(boxes_data, key=lambda x: x['xyxy'][0])
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# Remove similar boxes
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unique_sorted_boxes_data = [sorted_boxes_data[0]]
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for i in range(1, len(sorted_boxes_data)):
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current_box = sorted_boxes_data[i]
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prev_box = unique_sorted_boxes_data[-1]
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# Check if the current box's x-coordinate is significantly different from the previous box
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if abs(current_box['xyxy'][0] - prev_box['xyxy'][0]) > 1: # Adjust threshold as needed
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unique_sorted_boxes_data.append(current_box)
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for box in unique_sorted_boxes_data:
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label_name = box["label"]
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box_coords = box["xyxy"]
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detected_objects.append((box_coords))
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draw.rectangle(box_coords, outline="red")
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draw.text((box_coords[0], box_coords[1] - 10), label_name, fill="red")
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captcha_result += str(int(label_name[0]) - 2)
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img.show() # Display the image with bounding boxes and labels
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```
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## Training Details
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### Training Data
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Raw Pixel Digit Captcha Data []
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## Model Card Authors [optional]
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[Saidi Souhaieb]
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