Use PIL to eliminate chroma subsampling in crops (#7008)

* use pillow to save higher-quality jpg (w/o color subsampling)

* Cleanup and doc issue

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

utils/plots.py

@@ -458,7 +458,7 @@ def profile_idetection(start=0, stop=0, labels=(), save_dir=''):
     plt.savefig(Path(save_dir) / 'idetection_profile.png', dpi=200)
 
 
-def save_one_box(xyxy, im, file='image.jpg', gain=1.02, pad=10, square=False, BGR=False, save=True):
+def save_one_box(xyxy, im, file=Path('im.jpg'), gain=1.02, pad=10, square=False, BGR=False, save=True):
     # Save image crop as {file} with crop size multiple {gain} and {pad} pixels. Save and/or return crop
     xyxy = torch.tensor(xyxy).view(-1, 4)
     b = xyxy2xywh(xyxy)  # boxes
@@ -470,5 +470,7 @@ def save_one_box(xyxy, im, file='image.jpg', gain=1.02, pad=10, square=False, BG
     crop = im[int(xyxy[0, 1]):int(xyxy[0, 3]), int(xyxy[0, 0]):int(xyxy[0, 2]), ::(1 if BGR else -1)]
     if save:
         file.parent.mkdir(parents=True, exist_ok=True)  # make directory
-        cv2.imwrite(str(increment_path(file).with_suffix('.jpg')), crop)
+        f = str(increment_path(file).with_suffix('.jpg'))
+        # cv2.imwrite(f, crop)  # https://github.com/ultralytics/yolov5/issues/7007 chroma subsampling issue
+        Image.fromarray(cv2.cvtColor(crop, cv2.COLOR_BGR2RGB)).save(f, quality=95, subsampling=0)
     return crop