File size: 1,887 Bytes
0dc87cd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | """Crop detected product regions from shelf images."""
import cv2
import numpy as np
from pathlib import Path
def crop_detections(
image_path: str,
detections: list[dict],
output_dir: str = None,
padding: int = 5,
) -> list[dict]:
"""
Crop each detected bounding box from the shelf image.
Args:
image_path: path to the shelf image
detections: list of dicts with 'bbox' key ([x1, y1, x2, y2])
output_dir: if set, save crops as JPEGs
padding: pixels to add around each box (clamped to image bounds)
Returns:
Same detections list, each dict augmented with:
- 'crop': np.ndarray of the cropped region (BGR)
- 'crop_path': str path if output_dir was set
"""
img = cv2.imread(image_path)
h, w = img.shape[:2]
image_name = Path(image_path).stem
if output_dir:
Path(output_dir).mkdir(parents=True, exist_ok=True)
for i, det in enumerate(detections):
x1, y1, x2, y2 = [int(c) for c in det["bbox"]]
x1 = max(0, x1 - padding)
y1 = max(0, y1 - padding)
x2 = min(w, x2 + padding)
y2 = min(h, y2 + padding)
crop = img[y1:y2, x1:x2]
det["crop"] = crop
if output_dir:
crop_path = str(Path(output_dir) / f"{image_name}_crop_{i:03d}.jpg")
cv2.imwrite(crop_path, crop)
det["crop_path"] = crop_path
print(f"[cropper] Cropped {len(detections)} regions from {image_path}")
return detections
if __name__ == "__main__":
import sys
from detector import detect_products
path = sys.argv[1] if len(sys.argv) > 1 else "shelf_images/shelf_01.jpg"
out_dir = sys.argv[2] if len(sys.argv) > 2 else "outputs/crops"
dets = detect_products(path)
dets = crop_detections(path, dets, output_dir=out_dir)
print(f"Saved {len(dets)} crops to {out_dir}")
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