How to get Layer Outputs of CNN-CodePudding

I built a VGG16 model and trained it. I would like to see output of softmax layer (prediction probabilities) of this model for test images. I searched for answers and tried below code. It gives this error InvalidArgumentError: 2 root error(s) found. (0) INVALID_ARGUMENT: transpose expects a vector of size 3. But input(1) is a vector of size 4 [[{{node conv2d_26/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer}}]] [[conv2d_29/Relu/_311]] (1) INVALID_ARGUMENT: transpose expects a vector of size 3. But input(1) is a vector of size 4 [[{{node conv2d_26/Conv2D-0-TransposeNHWCToNCHW-LayoutOptimizer}}]] 0 successful operations. 0 derived errors ignored. Here is the code snippet below, I tried test image (224,244,3) and array of that image for the "image" variable. Still gives the same error. Any help is highly appreciated.

def get_all_outputs(model, input_data, learning_phase=1):
    outputs = [layer.output for layer in model.layers[1:]] # exclude Input
    layers_fn = K.function([model.input, K.learning_phase()], outputs)
    return layers_fn([input_data, learning_phase])

outputs = get_all_outputs(model, image, 1)

CodePudding user response：

you want to predict score of an image. model.predict passes your input image through the model and gives the score of your image.

model.predict(image)

CodePudding user response：

First save the model and then load the model like this

# # Save the model
filepath = './saved_model'
save_model(model, filepath)

# Load the model
model = load_model(filepath)

Then get the output for a test image like the following code

 Generate predictions for samples
predictions = model.predict(samples_to_predict)
print(predictions)

# Generate arg maxes for predictions
classes = np.argmax(predictions, axis = 1)
print(classes)