The repository contains a differentiable model of JPEG compression which can be useful in other research as well (see models.jpeg.DJPG). The model expresses successive steps of the codec as matrix multiplications or convolution layers (see papers for details) and supports the following approximations of DCT coefficient quantization:
None- uses standard rounding (backpropagation not supported)sin- sinusoidal approximation of the rounding operator (allows for back-propagation)soft- uses standard rounding in the forward pass and sinusoidal approximation in the backward passharmonic- a differentiable approximation with Taylor expansion
See the test script test_jpg.py for a standalone usage example. The following plot compares image quality and generated outputs for various approximation modes.
