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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)
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