glenn-jocher commited on
Commit
3373aab
·
unverified ·
1 Parent(s): e19f87e

NMS unused variable fix (#7161)

Browse files

* NMS unused variable fix

* Update general.py

Files changed (1) hide show
  1. utils/general.py +6 -7
utils/general.py CHANGED
@@ -703,7 +703,7 @@ def clip_coords(boxes, shape):
703
 
704
  def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False,
705
  labels=(), max_det=300):
706
- """Runs Non-Maximum Suppression (NMS) on inference results
707
 
708
  Returns:
709
  list of detections, on (n,6) tensor per image [xyxy, conf, cls]
@@ -718,18 +718,19 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non
718
  assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
719
 
720
  # Settings
721
- min_wh, max_wh = 2, 7680 # (pixels) minimum and maximum box width and height
 
722
  max_nms = 30000 # maximum number of boxes into torchvision.ops.nms()
723
  time_limit = 0.030 * bs # seconds to quit after
724
  redundant = True # require redundant detections
725
  multi_label &= nc > 1 # multiple labels per box (adds 0.5ms/img)
726
  merge = False # use merge-NMS
727
 
728
- t, warn_time = time.time(), True
729
  output = [torch.zeros((0, 6), device=prediction.device)] * bs
730
  for xi, x in enumerate(prediction): # image index, image inference
731
  # Apply constraints
732
- x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0 # width-height
733
  x = x[xc[xi]] # confidence
734
 
735
  # Cat apriori labels if autolabelling
@@ -790,9 +791,7 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non
790
 
791
  output[xi] = x[i]
792
  if (time.time() - t) > time_limit:
793
- if warn_time:
794
- LOGGER.warning(f'WARNING: NMS time limit {time_limit:3f}s exceeded')
795
- warn_time = False
796
  break # time limit exceeded
797
 
798
  return output
 
703
 
704
  def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False,
705
  labels=(), max_det=300):
706
+ """Non-Maximum Suppression (NMS) on inference results to reject overlapping bounding boxes
707
 
708
  Returns:
709
  list of detections, on (n,6) tensor per image [xyxy, conf, cls]
 
718
  assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0'
719
 
720
  # Settings
721
+ # min_wh = 2 # (pixels) minimum box width and height
722
+ max_wh = 7680 # (pixels) maximum box width and height
723
  max_nms = 30000 # maximum number of boxes into torchvision.ops.nms()
724
  time_limit = 0.030 * bs # seconds to quit after
725
  redundant = True # require redundant detections
726
  multi_label &= nc > 1 # multiple labels per box (adds 0.5ms/img)
727
  merge = False # use merge-NMS
728
 
729
+ t = time.time()
730
  output = [torch.zeros((0, 6), device=prediction.device)] * bs
731
  for xi, x in enumerate(prediction): # image index, image inference
732
  # Apply constraints
733
+ # x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0 # width-height
734
  x = x[xc[xi]] # confidence
735
 
736
  # Cat apriori labels if autolabelling
 
791
 
792
  output[xi] = x[i]
793
  if (time.time() - t) > time_limit:
794
+ LOGGER.warning(f'WARNING: NMS time limit {time_limit:.3f}s exceeded')
 
 
795
  break # time limit exceeded
796
 
797
  return output