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Allow multi_label option for NMS with PyTorch Hub (#4728)

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* Allow specifying multi_label option for NMS when using torch hub

* Reformat

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Jean-Baptiste MartinandGlenn Jocher authored and GitHub committed 2021-09-09 15:32:04 +02:00
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commit 1cad0ce2c7
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models/common.py
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@@ -278,6 +278,7 @@ class AutoShape(nn.Module):
conf = 0.25 # NMS confidence threshold conf = 0.25 # NMS confidence threshold
iou = 0.45 # NMS IoU threshold iou = 0.45 # NMS IoU threshold
classes = None # (optional list) filter by class classes = None # (optional list) filter by class
multi_label = False # NMS multiple labels per box
max_det = 1000 # maximum number of detections per image max_det = 1000 # maximum number of detections per image
def __init__(self, model): def __init__(self, model):
@@ -337,7 +338,8 @@ class AutoShape(nn.Module):
t.append(time_sync()) t.append(time_sync())
# Post-process # Post-process
y = non_max_suppression(y, self.conf, iou_thres=self.iou, classes=self.classes, max_det=self.max_det) # NMS y = non_max_suppression(y, self.conf, iou_thres=self.iou, classes=self.classes,
multi_label=self.multi_label, max_det=self.max_det) # NMS
for i in range(n): for i in range(n):
scale_coords(shape1, y[i][:, :4], shape0[i]) scale_coords(shape1, y[i][:, :4], shape0[i])