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| # test_detector.py | |
| from detector import detect_clothing | |
| from PIL import Image, ImageDraw | |
| import os | |
| def visualize_and_print(image_path, do_bg_remove=False, output_dir="vis"): | |
| # Ensure output folder exists | |
| os.makedirs(output_dir, exist_ok=True) | |
| img = Image.open(image_path).convert("RGB") | |
| print(f"\n--- Testing {os.path.basename(image_path)} (bg_remove={do_bg_remove}) ---") | |
| # Run your detector | |
| dets = detect_clothing(img, do_bg_remove=do_bg_remove) | |
| if not dets: | |
| print("No detections!") | |
| return | |
| # Print raw detections | |
| # Print raw detections | |
| for i, d in enumerate(dets.values(), 1): | |
| lbl = d["label"] | |
| scr = d["score"] | |
| box = d.get("box", []) | |
| print(f" {i}. {lbl:12s} @ {scr:.2f} → {box}") | |
| # Draw boxes | |
| vis = img.copy() | |
| draw = ImageDraw.Draw(vis) | |
| for d in dets.values(): | |
| if d.get("box"): | |
| x0, y0, x1, y1 = d["box"] | |
| draw.rectangle([x0, y0, x1, y1], outline="red", width=2) | |
| draw.text((x0, y0 - 10), f"{d['label']}:{d['score']:.2f}", fill="red") | |
| # Save visualization | |
| out_path = os.path.join(output_dir, os.path.basename(image_path)) | |
| vis.save(out_path) | |
| print(f" Visualization saved to {out_path}") | |
| if __name__ == "__main__": | |
| # List your test images here | |
| samples = [ | |
| "/Users/tanzimfarhan/Desktop/Python/Codes/SLU/CS5930/FinalProject/StyleSavvy/images/casual.jpg", | |
| "/Users/tanzimfarhan/Desktop/Python/Codes/SLU/CS5930/FinalProject/StyleSavvy/images/WomenCasual.jpg", | |
| ] | |
| for img_path in samples: | |
| visualize_and_print(img_path, do_bg_remove=False) | |
| # visualize_and_print(img_path, do_bg_remove=True) | |