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Winning solution in AIM 2019 RAW to RGB Mapping Challenge (ICCV2019W)
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models
.gitignore
README.md
dali_data.py
data.py
data_noise.py
psnr.py
readme.txt
result_ensemble.py
test-full.py
test-pad.py
test-val.py
test.py
train-noise.py
train.py
utils.py

README.md

RAW2RGBNet

This is a PyTorch implement of RAW2RGBNet. Our Team: The First Team of Hogwarts School got 22.34dB in the validation set. For more details please refer to the official website of the challenge: https://competitions.codalab.org/competitions/20158#results

Training

python train.py --name full_mix3_deep_encoder_decoder --model full_mix3_deep_encoder_decoder --batchSize 16 --data_root /data1/kangfu/Datasets/RAW2RGB/ --checkpoint /data1/kangfu/Checkpoints/RAW2RGB/ --cuda --size 64

Validation

python test-val.py --model mix3_deep_encoder_decoder --checkpoint /data1/kangfu/Checkpoints/RAW2RGB/mix3_deep_encoder_decoder_32_10_16_8_216_f_f_f/94.pth --output /data1/kangfu/Datasets/RAW2RGB/val_results --data /data1/kangfu/Datasets/RAW2RGB/RAW/

python psnr.py --data /data1/kangfu/Datasets/RAW2RGB/val_results --gt /data1/kangfu/Datasets/RAW2RGB/RGB/

Testing

CUDA_VISIBLE_DEVICES=0 python test.py --model mix3_deep_encoder_decoder --checkpoint ./80.pth --output /data1/kangfu/Datasets/RAW2RGB/val_results --data ~/ram_data/RAW2RGB/Validation

Testing Full-Resolution Images on Single Titan XP (12GB)

CUDA_VISIBLE_DEVICES=0 python test-pad.py --model full_mix3_deep_encoder_decoder --checkpoint ./112.pth --output /data1/kangfu/Datasets/RAW2RGB/testing_full_results_full_mix3_bacth_224_ep_112  --data /data1/kangfu/Datasets/RAW2RGB/FullResTestingPhoneRaw

Testing Full-Resolution Images on Single Tesla M40 (24GB)

python3 test-full.py --model full_mix3_deep_encoder_decoder --checkpoint ./114.pth --output ../testing_full_results_full_mix3_bacth_224_ep_114  --data ../FullResTestingPhoneRaw/

Reproduce results in the challenge submission

You can download the pre-trained model from here 114.pth 115.pth

# For track 1
# generate results using the 114.pth and the 115.pth respectively
python test.py --model full_mix3_deep_encoder_decoder --checkpoint ./114.pth --output /data1/kangfu/Datasets/RAW2RGB/validation_results_full_mix3_bacth_224_ep_114 --data /data1/kangfu/Datasets/RAW2RGB/Validation

python test.py --model full_mix3_deep_encoder_decoder --checkpoint ./115.pth --output /data1/kangfu/Datasets/RAW2RGB/validation_results_full_mix3_bacth_224_ep_115--data /data1/kangfu/Datasets/RAW2RGB/Validation

# ensemble the results from 104.pth and 105.pth
python result_ensemble.py --data /data1/kangfu/Datasets/RAW2RGB/testing_results_full_mix3_bacth_224_ep_114,/data1/kangfu/Datasets/RAW2RGB/testing_results_full_mix3_bacth_224_ep_115 --output /data1/kangfu/Datasets/RAW2RGB/testing_results_ensemble_114_115

# For track 2
# generate results using the 115.pth only
python3 test-full.py --model full_mix3_deep_encoder_decoder --checkpoint ./115.pth --output ../testing_full_results_full_mix3_bacth_224_ep_114  --data ../FullResTestingPhoneRaw/

Contact

If you have any questions about the code, please contact kangfumei@link.cuhk.edu.cn

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