gluoncv-Faster RCNN打印预测标签

Question

我修改了original [gluoncv.utils.viz.bbox]以打印类标签。但是，为什么不遍历所有bbox？最后，我要实现的是计算已识别对象的数量。

以下是我尝试的代码。

def Test(img, bboxes, scores=None, labels=None, thresh=0.5,
              class_names=None, colors=None, ax=None,
              reverse_rgb=False, absolute_coordinates=True):

    from matplotlib import pyplot as plt

    if labels is not None and not len(bboxes) == len(labels):
        raise ValueError('The length of labels and bboxes mismatch, {} vs {}'
                         .format(len(labels), len(bboxes)))
    if scores is not None and not len(bboxes) == len(scores):
        raise ValueError('The length of scores and bboxes mismatch, {} vs {}'
                         .format(len(scores), len(bboxes)))


    if isinstance(bboxes, mx.nd.NDArray):
        bboxes = bboxes.asnumpy()
    if isinstance(labels, mx.nd.NDArray):
        labels = labels.asnumpy()
    if isinstance(scores, mx.nd.NDArray):
        scores = scores.asnumpy()


    for i, bbox in enumerate(bboxes):
        if scores is not None and scores.flat[i] < thresh:
            continue
        if labels is not None and labels.flat[i] < 0:
            continue
        cls_id = int(labels.flat[i]) if labels is not None else -1

        if class_names is not None and cls_id < len(class_names):
            class_name = class_names[cls_id]
        else:
            class_name = str(cls_id) if cls_id >= 0 else ''
        score = '{:.3f}'.format(scores.flat[i]) if scores is not None else ''
        if class_name or score:
            t = '{:s} {:s}'.format(class_name, score)
    return t

box_ids, scores, bboxes = net(x)
ab = Test(orig_img, bboxes[0], scores[0], box_ids[0], class_names=net.classes)
print(ab)