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The official codebase for the Learned Smartphone ISP Challenge in MAI @ CVPR 2021

Home Page: https://arxiv.org/abs/2105.07809

License: Apache License 2.0

Python 8.46% Shell 0.05% Jupyter Notebook 91.49%
cvpr2021 deep-learning smartphone-isp computer-vision tensorflow cvpr low-level-vision python tflite mediatek

mai21-learned-smartphone-isp's Issues

Doubt on VGG19 features on the RAW images

This line suggests it's using a pre-trained VGG19 on the RAW images to extract meaningful representations.

How come a model pre-trained on 3 channel images is being used here for this purpose?

Any clarification would be helpful.

How was the validation data obtained?

Hi folks,

I am trying to get the provided code running. Wanted to know how was the validation split obtained? Was it obtained from the original training pairs (RAW-RGB)?

Pre-trained Model

Where can i download pre-trained model for inference? Though it has been mentioned that "Download Mediatek's pre-trained PUNET model and put it into models/original/ folder" but i could not find the link. You help would be much appreciated.

Happy to work on Colab Notebook

Hi folks.

Huge thanks for organizing this. I am a MobileML practitioner and have experience with many deep learning models that are mobile-friendly. Some projects:

I wanted to know if you folks would be up if submitted a Colab Notebook showing the model conversion and inference process in TensorFlow Lite. This way I think the community will be able to play with the pre-trained models quickly.

Mismatch between training and inference

The training happens with 128x128 (reduced) RAW images while the pre-trained model's input dimensions are different. Why is this mismatch? I understand the pre-trained model's input dimensions have been matched to what's expected in the challenge. But I feel I am missing out on something here.

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