From ab75922e93dcfd1455172a99901b48f344e705d4 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Sat, 26 Mar 2022 16:52:58 +0100 Subject: [PATCH] NMS unused variable fix (#7161) * NMS unused variable fix * Update general.py --- utils/general.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/utils/general.py b/utils/general.py index 4322c71257d..a8181bbaf5e 100755 --- a/utils/general.py +++ b/utils/general.py @@ -707,7 +707,7 @@ def clip_coords(boxes, shape): def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False, labels=(), max_det=300): - """Runs Non-Maximum Suppression (NMS) on inference results + """Non-Maximum Suppression (NMS) on inference results to reject overlapping bounding boxes Returns: list of detections, on (n,6) tensor per image [xyxy, conf, cls] @@ -722,18 +722,19 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non assert 0 <= iou_thres <= 1, f'Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0' # Settings - min_wh, max_wh = 2, 7680 # (pixels) minimum and maximum box width and height + # min_wh = 2 # (pixels) minimum box width and height + max_wh = 7680 # (pixels) maximum box width and height max_nms = 30000 # maximum number of boxes into torchvision.ops.nms() time_limit = 0.030 * bs # seconds to quit after redundant = True # require redundant detections multi_label &= nc > 1 # multiple labels per box (adds 0.5ms/img) merge = False # use merge-NMS - t, warn_time = time.time(), True + t = time.time() output = [torch.zeros((0, 6), device=prediction.device)] * bs for xi, x in enumerate(prediction): # image index, image inference # Apply constraints - x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0 # width-height + # x[((x[..., 2:4] < min_wh) | (x[..., 2:4] > max_wh)).any(1), 4] = 0 # width-height x = x[xc[xi]] # confidence # Cat apriori labels if autolabelling @@ -794,9 +795,7 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non output[xi] = x[i] if (time.time() - t) > time_limit: - if warn_time: - LOGGER.warning(f'WARNING: NMS time limit {time_limit:3f}s exceeded') - warn_time = False + LOGGER.warning(f'WARNING: NMS time limit {time_limit:.3f}s exceeded') break # time limit exceeded return output