updates
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@ -294,7 +294,7 @@ def build_targets(target, anchor_wh, nA, nC, nG):
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def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
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"""
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Removes detections with lower object confidence score than 'conf_thres' and performs
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Removes detections with lower object confidence score than 'conf_thres'
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Non-Maximum Suppression to further filter detections.
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Returns detections with shape:
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(x1, y1, x2, y2, object_conf, class_score, class_pred)
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@ -369,7 +369,7 @@ def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
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if prediction.is_cuda:
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unique_labels = unique_labels.cuda(prediction.device)
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nms_style = 'OR' # 'AND' or 'OR' (classical)
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nms_style = 'OR' # 'AND', 'OR' (classical), 'MERGE' (experimental)
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for c in unique_labels:
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# Get the detections with the particular class
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det_class = detections[detections[:, -1] == c]
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