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can tf-expain explain tf-lite models?
if can, how to explain?
if not, would you have some advice or suggestion?
The text was updated successfully, but these errors were encountered:
I fig it out, would you please check this idea is right?
I rewrite a OcclusionSensitivity class and use python read tf.lite model then predict
the key codes:
` def get_sensitivity_map(self, interpreter, image, class_index, patch_size): # interpreter is tf.lite model ... interpreter.allocate_tensors() for patch in tqdm(patches): interpreter.set_tensor(interpreter.get_input_details()[0]['index'], [patch]) interpreter.invoke() preds = interpreter.get_tensor(interpreter.get_output_details()[0]['index']) predictions.extend(preds)
target_class_predictions = [ prediction[class_index] for prediction in predictions ] ...
`
beacause I can't find how to batch predict image use tf.lite model, so I make a for loop and set a bigger patch_size
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can tf-expain explain tf-lite models?
if can, how to explain?
if not, would you have some advice or suggestion?
The text was updated successfully, but these errors were encountered: