lightweightopenpose,骨架可视化

在demo文件里改，在run_demo函数里

改后的run_demo如下：

def run_demo(net, image_provider, height_size, cpu, track, smooth):
    net = net.eval()
    #if not cpu:
        #net = net.cuda()

    stride = 8  # 卷积步长
    upsample_ratio = 4
    num_keypoints = Pose.num_kpts  # 18
    previous_poses = []
    delay = 1
    i = 0

    for img in image_provider:  # 图像/视频文件
        i += 1
        orig_img = img.copy()
        sk_img = np.zeros(img.shape)
        heatmaps, pafs, scale, pad = infer_fast(net, img, height_size, stride, upsample_ratio, cpu)

        # 记录总共检测到的关键点个数
        total_keypoints_num = 0
        # [x,y,conf,id] ， 从extract_keypoints函数里返回
        all_keypoints_by_type = []
        for kpt_idx in range(num_keypoints):  # 19th for bg 19种连接方向（线段）
            # 提取第i个关键点的个数,把关键点的[x,y,conf,id]加入到all_keypoints_by_type
            # 关键点个数使用total_keypoints_num记录
            total_keypoints_num += extract_keypoints(heatmaps[:, :, kpt_idx], all_keypoints_b