72 def filter_boxes(boxes, box_confidences, box_class_probs):  argument
85     boxes = boxes.reshape(-1, 4)
90     boxes = boxes[_box_pos]
98     boxes = boxes[_class_pos]
102     return boxes, classes, scores
105 def nms_boxes(boxes, scores):  argument
115     x = boxes[:, 0]
116     y = boxes[:, 1]
117     w = boxes[:, 2] - boxes[:, 0]
118     h = boxes[:, 3] - boxes[:, 1]
149     boxes, classes, scores = [], [], []
153         boxes.append(b)
157     boxes = np.concatenate(boxes)
158     boxes = xywh2xyxy(boxes)
165         b = boxes[inds]
178     boxes = np.concatenate(nboxes)
182     return boxes, classes, scores
185 def draw(image, boxes, scores, classes):  argument
195     for box, score, cl in zip(boxes, scores, classes):
307     boxes, classes, scores = yolov5_post_process(input_data)  variable
310     if boxes is not None:
311         draw(img_1, boxes, scores, classes)