yolo_model.predict返回的是tensor，但我后续做cpu_nms时要求输入的是ndarray类型，我尝试过用.eval()（可能是我写的不对？），但是会出现FailedPreconditionError的错误

img = np.asarray(img, np.float32)
img = img[np.newaxis, :] / 255.


with tf.Session() as sess:

    input_data = tf.placeholder(tf.float32, [1, args.new_size[1], args.new_size[0], 3], name='input_data')
    yolo_model = yolov3(args.num_class, args.anchors)
    with tf.variable_scope('yolov3'):
        pred_feature_maps = yolo_model.forward(input_data, False)

    pred_boxes, pred_confs, pred_probs = yolo_model.predict(pred_feature_maps)

    pred_scores = pred_confs * pred_probs
    # pred_boxes = pred_boxes.eval()
    # pred_scores = pred_scores.eval()

    boxes, scores, labels = cpu_nms(pred_boxes, pred_scores, args.num_class, max_boxes=200, score_thresh=0.3, iou_thresh=0.45)

    saver = tf.train.Saver()
    saver.restore(sess, args.restore_path)

    boxes_, scores_, labels_ = sess.run([boxes, scores, labels], feed_dict={input_data: img})

谢谢