我有一个脚本,它会遮盖图片的一部分并通过预测网络运行它,以查看哪些部分最强烈地影响标签预测。为此,我使用PIL打开本地图像并调整大小,同时在各个间隔处添加黑色框。我使用Tensorflow打开我的模型,并想将图像传递给模型,但它不期望具有这种特定形状的值:
Traceback (most recent call last):
File "obscureImage.py", line 55, in <module>
originalPrediction, originalTag = predict(originalImage, labels)
File "obscureImage.py", line 23, in predict
{'DecodeJpeg/contents:0': image})
File "C:\Users\User\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 766, in run
run_metadata_ptr)
File "C:\Users\User\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 943, in _run
% (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (224, 224, 3) for Tensor 'DecodeJpeg/contents:0', which has shape '()'
这是我的代码:
def predict(image, labels):
with tf.Session() as sess:
#image_data = tf.gfile.FastGFile(image, 'rb').read() # What I used to use.
softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
predictions = sess.run(softmax_tensor,
{'DecodeJpeg/contents:0': image})
predictions = np.squeeze(predictions)
top_k = predictions.argsort()[-5:][::-1] # Getting top 5 predictions
return predictions[0], labels[top_k[0]] # Return the raw value of tag matching and the matching tag.
originalImage = Image.open(args.input).resize((args.imgsz,args.imgsz)).convert('RGB')
originalPrediction, originalTag = predict(originalImage, labels)
从磁盘打开并使用图像可以正常工作,但当然这不是我的修改后的图像。我尝试将 tf.image.decode_jpeg(image,0)
用作 softmax 张量的参数,但它会导致 TypeError: Expected string passed to parameter 'contents' of op 'DecodeJpeg', got <PIL.Image.Image image mode=RGB size=224x224 at 0x2592F883358> of type 'Image' instead.