python - decode_predictions on a saved keras model -


i using keras train model on images , saving .h5 file.

i use predict() predictions model works fine. when try decode predictions labels , probability using decode_predictions throws error:

`decode_predictions` expects batch of predictions (i.e. 2d array of shape (samples, 1000)). found array shape: (1, 2) ]

this use load model:

model = load_model(self._model_path) model.load_weights(self._model_weights)

and features , decode them:

img = image.load_img(image_path, target_size=self._target_size) x = image.img_to_array(img) x = x.transpose(1, 0, 2) x = np.expand_dims(x, axis=0) x = preprocess_input(x) features = model.predict(x) predictions = decode_predictions(features, top=3)

is not possible decode_predictions on models not pre_trained on imagenet? model load vgg16 model top layer removed , retrained on new images.

is there way labels such models? thanks


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