Prediction results are the same in inference

[gantians]

I just use the pretrained model to predict my own data without training. The model is NetVLADModelLF.

I only extract rgb features on my own data and construct input tensor.

for i in xrange(data_num): 
        feature = data[i]
        pad_feature = np.zeros([300, 1152])
        pad_feature[0, :1024] = feature
        video_batch = pad_feature[np.newaxis, :, :].astype(np.float32)
        num_frames_batch = np.array([1], dtype=np.int32)
        predictions = sess.run([predictions_tensor],
                        feed_dict={input_tensor: video_batch, num_frames_tensor: num_frames_batch})

The predictions are the same. I tried to construct 300 frame input but the problems remains.

Did i do the inference correctly?