Parameterize max_det + inference default at 1000 (#3215)
* Added max_det parameters in various places * 120 character line * PEP8 * 120 character line * Update inference default to 1000 instances * Update inference default to 1000 instances Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@@ -482,7 +482,7 @@ def wh_iou(wh1, wh2):
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def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=None, agnostic=False, multi_label=False,
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labels=()):
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labels=(), max_det=300):
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"""Runs Non-Maximum Suppression (NMS) on inference results
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Returns:
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@@ -498,7 +498,6 @@ def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, classes=Non
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# Settings
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min_wh, max_wh = 2, 4096 # (pixels) minimum and maximum box width and height
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max_det = 300 # maximum number of detections per image
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max_nms = 30000 # maximum number of boxes into torchvision.ops.nms()
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time_limit = 10.0 # seconds to quit after
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redundant = True # require redundant detections
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