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--- |
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license: cc-by-nc-sa-4.0 |
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pipeline_tag: object-detection |
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tags: |
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- yolov8 |
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- object-detection |
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datasets: |
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- MichalMlodawski/closed-open-eyes |
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language: |
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- en |
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--- |
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**Links to Space:** |
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https://huggingface.co/spaces/MichalMlodawski/closed-open-eyes-detection |
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**Eval:** |
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| Epoch | Train Box Loss | Train Cls Loss | Train DFL Loss | Precision (B) | Recall (B) | mAP50 (B) | mAP50-95 (B) | Val Box Loss | Val Cls Loss | Val DFL Loss | LR PG0 | LR PG1 | LR PG2 | |
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|-------|----------------|----------------|----------------|---------------|------------|-----------|--------------|--------------|--------------|--------------|--------|--------|--------| |
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| 100 | 1.0201 | 0.4718 | 0.84219 | 0.95394 | 0.93356 | 0.96767 | 0.66184 | 0.98246 | 0.45574 | 0.83703 | 0.000199 | 0.000199 | 0.000199 | |
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**Example code to run the model:** |
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import os |
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from pathlib import Path |
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from ultralytics import YOLO |
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import cv2 |
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import logging |
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import argparse |
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def setup_logging(): |
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logging.basicConfig(level=logging.INFO, |
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format='%(asctime)s - %(levelname)s - %(message)s') |
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def process_images(model_path, test_images_path): |
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try: |
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# Path to the results directory |
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results_path = os.path.join(test_images_path, 'result') |
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# Create the results folder |
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os.makedirs(results_path, exist_ok=True) |
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logging.info(f'Created results directory: {results_path}') |
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# Load the model |
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model = YOLO(model_path) |
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logging.info(f'Loaded model from: {model_path}') |
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# Process images |
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for img_file in Path(test_images_path).glob('*.*'): |
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if img_file.suffix.lower() in ['.jpg', '.jpeg', '.png']: # Supports JPG, JPEG, and PNG formats |
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logging.info(f'Processing file: {img_file}') |
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# Detect objects in the image |
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results = model(img_file) |
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for result in results: |
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# Get the result image with detections drawn |
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result_img = result.plot() |
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# Save the result image to the results_path folder |
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result_image_path = os.path.join(results_path, img_file.name) |
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cv2.imwrite(result_image_path, result_img) |
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logging.info(f'Saved result image to: {result_image_path}') |
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logging.info("Image processing completed.") |
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except Exception as e: |
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logging.error(f'An error occurred: {e}') |
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def main(): |
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parser = argparse.ArgumentParser(description='Process images using YOLO model.') |
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parser.add_argument('model_path', type=str, help='Path to the YOLO model.') |
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parser.add_argument('test_images_path', type=str, help='Path to the directory containing test images.') |
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args = parser.parse_args() |
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setup_logging() |
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process_images(args.model_path, args.test_images_path) |
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if __name__ == "__main__": |
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main() |
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**Command to run the program:** |
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python script_name.py path/to/your/yolo_model.pt path/to/test/images |
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