Tensorflow prediciton error, invalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]

Question

I trained a Tensorflow Ssd object-detection model using Google object-detection Api and i exported the trained model using the provided "export_inference_graph.py" script as "Saved_model.pb" file with "encoded_image_string_tensor" as input type, however when i tried to make prediction to the model,

 i got the following error:
tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]

İ loaded the model into a graph as follow:
with tf.Session() as sess:
tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.SERVING], saved_model_file)
graph = tf.get_default_graph()

And made the prediction as follow:
# Convert the image into base64 encoded string
img = Image.open(IMAGE_PATH) resized_img = img.resize((300, 300),
Image.ANTIALIAS) binary_io = io.BytesIO() resized_img.save(binary_io, "JPEG")
bytes_string_image = base64.b64encode(binary_io.getvalue()).decode("utf-8")

# Define the input and output placeholder tensors
input_tensor = graph.get_tensor_by_name('encoded_image_string_tensor:0')
tensor_dict = {}
for key in ['num_detections', 'detection_boxes', 'detection_scores', 'detection_classes']:
tensor_name = key + ':0' tensor_dict[key] = graph.get_tensor_by_name(tensor_name)

# Finally, do the prediction
output_dict = sess.run(tensor_dict, feed_dict={ input_tensor: bytes_string_image})

Gufran Mirza · Accepted Answer

Can you check the value of bytes_string_image?

Ednsquare · Answer

Why are you converting it to base64 ? Can't you just use OpeCV to load the image ? Here is a good working example that i've tried in the past using OpenCV https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10/blob/master/Object_detection_image.py

Lex Hoffman · Answer

Actually, i don't have "image_tensor:0" in my graph. i just have "encoded_image_string_tensor"

Tensorflow

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