Resource retrieval

Retrieve the resource object:

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Get the pre-trained net:

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Basic usage

This net outputs a 64x64 heat map for each of the 68 landmarks:

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Obtain the dimensions of the heat map:

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Visualize heat maps 1, 12 and 29:

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Evaluation function

Write an evaluation function that picks the maximum position of each heat map and returns a list of landmark positions:

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Landmark positions

Get the landmarks using the evaluation function. Coordinates are rescaled to the input image size so that the bottom-left corner is identified by {0, 0} and the top-right corner by {1, 1}:

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Group landmarks associated with different facial features by colors:

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Visualize the landmarks:

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Preprocessing

The net must be evaluated on facial crops only. Get an image with multiple faces:

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Write an evaluation function that crops the input image around faces and returns the crops and facial landmarks:

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Evaluate the function on the image:

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Visualize the landmarks:

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Robustness to facial crop size

Get an image:

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Crop the image at various sizes:

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Inspect the network performance across the crops:

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Net information

Inspect the number of parameters of all arrays in the net:

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Obtain the total number of parameters:

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Obtain the layer type counts:

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Display the summary graphic:

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Export to MXNet

Export the net into a format that can be opened in MXNet:

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Export also creates a net.params file containing parameters:

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Get the size of the parameter file:

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The size is similar to the byte count of the resource object:

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