[Updata] fix bug

oneflow_yolov3/model/yolo_net.py

@@ -33,11 +33,11 @@ yolo_box_diff_conf = [{'image_height': image_height, 'image_width': image_width,
                        'anchor_boxes_size': anchor_boxes_size_list, 'box_mask': [0, 1, 2]}]
 
 # to confirm wh pos, gr 12.19 check with 11 ~/yolov3/predict.job
-yolo_conf = [{'layer_height': 19, 'layer_width': 19, 'prob_thresh': 0.005, 'num_classes': 80,
+yolo_conf = [{'layer_height': 19, 'layer_width': 19, 'prob_thresh': 0.00001, 'num_classes': 80,
               'anchor_boxes_size': [116, 90, 156, 198, 373, 326]},
-             {'layer_height': 38, 'layer_width': 38, 'prob_thresh': 0.005, 'num_classes': 80,
+             {'layer_height': 38, 'layer_width': 38, 'prob_thresh': 0.00001, 'num_classes': 80,
               'anchor_boxes_size': [30, 61, 62, 45, 59, 119]},
-             {'layer_height': 76, 'layer_width': 76, 'prob_thresh': 0.005, 'num_classes': 80,
+             {'layer_height': 76, 'layer_width': 76, 'prob_thresh': 0.00001, 'num_classes': 80,
               'anchor_boxes_size': [10, 13, 16, 30, 33, 23]}]
 
 
@@ -223,7 +223,8 @@ def YoloPredictLayer(in_blob, origin_image_info, i, trainable):
     [out_bbox, out_probs, valid_num] = yolo_detect(bbox=position, probs=confidence, origin_image_info=origin_image_info,
                                                    image_height=608, image_width=608,
                                                    layer_height=yolo_conf[i]['layer_height'],
-                                                   layer_width=yolo_conf[i]['layer_width'], prob_thresh=0.005,
+                                                   layer_width=yolo_conf[i]['layer_width'],
+                                                   prob_thresh=0.00001,
                                                    num_classes=80, max_out_boxes=max_out_boxes,
                                                    anchor_boxes=yolo_conf[i]['anchor_boxes_size'],
                                                    name=str(layer_name) + "yolo_detect")

oneflow_yolov3/model/yolo_test_python.py

@@ -166,12 +166,13 @@ if __name__ == "__main__":
                         continue
                     # Best iou, index between pred and targets
                     m = (pcls == tcls_tensor)
+                    m = np.nonzero(np.asarray(m))[0]
                     iou = utils.bboxes_iou(pbox, tbox[m])
                     bi = np.argmax(iou)
                     maxiou = iou[bi]
 
                     # If iou > threshold and class is correct mark as correct
-                    if maxiou > args.iou_thres:  # and pcls == tcls[bi]:
+                    if maxiou > args.iou_thres and m[bi] not in detected:  # and pcls == tcls[bi]:
                         correct[i] = 1
                         detected.append(m[bi])