This easy-to-use app proves that it is possible to run state of the art Deep Learning-based image compression algorithms on a resource-constrained device. The app features Deep Learning-based image encoder, decoder as well as an Entropy encoder to generate a comparable bitstream to traditional image compression algorithms.
The Deep Learning models used in the app are trained used InterDigital’s open source CompressAI project (https://github.com/InterDigitalInc/CompressAI) which is a Pytorch library and evaluation platform for end-to-end compression research. Pytorch versions of these models are available in the CompressAI model Zoo.
The app features a slick slider-based mechanism for comparing the visual quality of the compressed image generated from the Deep Learning based models as well as traditional image compression approaches like JPEG and HEIC.
The Deep Learning models used in the app are trained used InterDigital’s open source CompressAI project (https://github.com/InterDigitalInc/CompressAI) which is a Pytorch library and evaluation platform for end-to-end compression research. Pytorch versions of these models are available in the CompressAI model Zoo.
The app features a slick slider-based mechanism for comparing the visual quality of the compressed image generated from the Deep Learning based models as well as traditional image compression approaches like JPEG and HEIC.
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