Initialized

README.md

@@ -0,0 +1,94 @@
+## One-click script
+Make sure you are in the root folder. You should also have `tensorflow(-gpu)>=1.12.0` and `pytorch>=1.0.0` installed manually.
+
+Before running `one_click_ntire19_rsr.sh` for Real Image Super Resolution, set two paths: `RSR_TEST_DIR` for testing images and `RSR_SAVE_DIR` for saving results.
+```bash
+RSR_TEST_DIR=bla/bla/bla
+RSR_SAVE_DIR=bli/bli/bli
+. one_click_ntire19_rsr.sh
+```
+
+Before running `one_click_ntire19_drn.sh` for sRGB Image Denoising, set two paths: `DRN_TEST_MAT` for testing mat file and `DRN_SAVE_DIR` for saving results.
+```bash
+DRN_TEST_MAT=bla/bla/bla/BenchmarkNoisyBlocksSrgb.mat
+DRN_SAVE_DIR=bli/bli/bli
+. one_click_ntire19_drn.sh
+```
+
+You can also do it step-by-step as follows.
+
+## Step by step reproduce instructions
+
+1. Install the whole VSR package and its requirements:
+    ```bash
+    git clone https://github.com/LoSealL/VideoSuperResolution -b ntire_2019 && cd VideoSuperResolution
+    pip install -e .
+    ```
+    Note that you should pre-install `tensorflow` and `pytorch`.
+
+2. Download the pre-trained model:
+
+   **make sure you are in the root folder.*
+
+   For Real Image Super-Resolution
+   ```bash
+   python prepare_data.py --filter=rsr -q
+   ```
+
+   For sRGB Real Image Denoising (Track #2: sRGB)
+   ```bash
+   python prepare_data.py --filter=drn -q
+   ```
+
+   Model url for manually download:
+   - [rsr](https://github.com/LoSealL/Model/releases/download/crdn/rsr.zip): https://github.com/LoSealL/Model/releases/download/crdn/rsr.zip
+   - [drn](https://github.com/LoSealL/Model/releases/download/mldn/drn.zip): https://github.com/LoSealL/Model/releases/download/mldn/drn.zip
+
+3. Prepare testing data:
+
+   **make sure you are in the root folder.*
+
+   For RSR:
+
+   You need to crop images into small patches by:
+   ```bash
+   python VSR/Tools/DataProcessing/NTIRE19RSR.py --ref_dir=path/to/test/data/folder --patch_size=768 --stride=760 --save_dir=path/to/saving/folder
+   ```
+
+   For sRGB Denoising:
+
+   You need to convert .MAT file to png images by:
+   ```bash
+   python VSR/Tools/DataProcessing/NTIRE19Denoise.py --validation=path/to/.MAT --save_dir=path/to/saving/folder
+   ```
+
+4. Predicting
+
+   **make sure you are in the root folder.*
+
+   For RSR:
+   Entering VSRTorch folder
+   ```bash
+   cd VSRTorch
+   python eval.py rsr --cuda -t=/path/to/divided/test/images/folder --ensemble --pth=../Results/rsr/save/rsr_ep2000.pth
+   ```
+   The output will be saved in `../Results/rsr/<your-image-folder-name>`. To combine them back together:
+   ```bash
+   cd ..
+   python VSR/Tools/DataProcessing/NTIRE19RSR.py --ref_dir=path/to/test/data/folder --patch_size=768 --stride=760 --results=Results/rsr/<your-image-folder>/ --save_dir=path/to/saving/folder
+   ```
+   Where `--ref_dir` should keep the same as the folder in step 3, it's a reference to know how to combine patches. `--patch_size` and `--stride` should also keep the same.
+   
+   For sRGB Denoising:
+   Entering VSRTorch folder
+   ```bash
+   cd VSRTorch
+   python eval.py drn --cuda -t=/path/to/divided/test/images/folder --pth=../Results/drn/save/drn_ep2000.pth --output_index=0
+   ```
+   The output will be saved in `../Results/drn/<your-image-folder-name>`. To pack them into mat file:
+   ```bash
+   cd ..
+   python VSR/Tools/DataProcessing/NTIRE19Denoise.py --results=Results/drn/<your-image-folder-name>
+   ```
+   
+   *If OOM happened, try not to enable `--cuda` flag.

one_click_ntire19_drn.sh

@@ -0,0 +1,24 @@
+#!/usr/bin/env bash
+
+#DRN_TEST_MAT=
+#DRN_SAVE_DIR=
+
+git clone https://github.com/LoSealL/VideoSuperResolution -b ntire_2019 && cd VideoSuperResolution
+
+if [ ! -e setup.py ];
+then
+  echo " [!] Can't find setup.py file! Make sure you are in the right place!"
+fi
+
+echo "DRN_TEST_MAT=${DRN_TEST_MAT}"
+echo "DRN_SAVE_DIR=${DRN_SAVE_DIR}"
+
+pip install -e .
+python prepare_data.py --filter=drn -q
+echo " [*] Model extracted into Results/drn/save"
+python VSR/Tools/DataProcessing/NTIRE19Denoise.py --validation=${DRN_TEST_MAT} --save_dir=${DRN_SAVE_DIR}/1/
+pushd VSRTorch
+python eval.py drn --cuda -t=../${DRN_SAVE_DIR}/1/ --output_index=0
+popd
+python VSR/Tools/DataProcessing/NTIRE19Denoise.py --results=Results/drn/1/ --save_dir=${DRN_SAVE_DIR}/2/
+echo " [*] Processing done. Results are in ${DRN_SAVE_DIR}/2/"

one_click_ntire19_rsr.sh

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+
+#RSR_TEST_DIR=
+#RSR_SAVE_DIR=
+_PATCH_SIZE=768
+_STRIDE=760
+
+git clone https://github.com/LoSealL/VideoSuperResolution -b ntire_2019 && cd VideoSuperResolution
+
+if [ ! -e setup.py ];
+then
+  echo " [!] Can't find setup.py file! Make sure you are in the right place!"
+fi
+
+echo "RSR_TEST_DIR=${RSR_TEST_DIR}"
+echo "RSR_SAVE_DIR=${RSR_SAVE_DIR}"
+
+pip install -e .
+python prepare_data.py --filter=rsr -q
+echo " [*] Model extracted into Results/rsr/save"
+python VSR/Tools/DataProcessing/NTIRE19RSR.py --ref_dir=${RSR_TEST_DIR} --patch_size=${_PATCH_SIZE} --stride=${_STRIDE} --save_dir=${RSR_SAVE_DIR}/1/
+pushd VSRTorch
+python eval.py rsr --cuda --ensemble -t=../${RSR_SAVE_DIR}/1/
+popd
+python VSR/Tools/DataProcessing/NTIRE19RSR.py --ref_dir=${RSR_TEST_DIR} --patch_size=${_PATCH_SIZE} --stride=${_STRIDE} --results=Results/rsr/1/ --save_dir=${RSR_SAVE_DIR}/2/
+echo " [*] Processing done. Results are in ${RSR_SAVE_DIR}/2/"