I have a script that obscures part of an image and runs it through a prediction net to see which parts of the image most strongly influence the tag prediction. To do this, I open a local image with PIL and resize it, along with adding a black box at various intervals. I use Tensorflow to open my model and I want to pass the image to the model, but it's not expecting a value with this specific shape:

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 runrun_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 '()'

This is my code:

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 predictionsreturn 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)

Opening and using the image from the disk works fine, but of course then it's not my modified image. I tried using tf.image.decode_jpeg(image,0) as the parameter for the softmax tensor, but that gives me 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.

Use the img_to_array function from Keras:

import tensorflow as tf 
from PIL import Imagepil_img = Image.new(3, (200, 200))
image_array  = tf.keras.utils.img_to_array(pil_img)