Update README.md

Author: 2KangHo

README.md

@@ -13,7 +13,46 @@ And you can input gaussian noise to input images.
 1. Download [DF2K dataset](https://drive.google.com/file/d/1P9pcaGjvq3xiF22GXIq7ciZta3rjZxaY/view?usp=sharing). Or other dataset is ok, but directory hierarchy -> `<NAME>/train/`, `<NAME>/valid/`
 2. move under dataset directory (i.e. `vdsr_pytorch/dataset/DF2K`)
 
-## Training
+## Usage
+### Training & Evaluation
+```
+usage: main.py [-h] --dataset DATASET --crop_size CROP_SIZE
+               --upscale_factor UPSCALE_FACTOR [--batch_size BATCH_SIZE]
+               [--test_batch_size TEST_BATCH_SIZE] [--epochs EPOCHS] [--lr LR]
+               [--step STEP] [--clip CLIP] [--weight-decay WEIGHT_DECAY]
+               [--cuda] [--threads THREADS] [--gpuids GPUIDS [GPUIDS ...]]
+               [--add_noise] [--noise_std NOISE_STD] [--test] [--model PATH]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --dataset DATASET     dataset directory name
+  --crop_size CROP_SIZE
+                        network input size
+  --upscale_factor UPSCALE_FACTOR
+                        super resolution upscale factor
+  --batch_size BATCH_SIZE
+                        training batch size
+  --test_batch_size TEST_BATCH_SIZE
+                        testing batch size
+  --epochs EPOCHS       number of epochs to train for
+  --lr LR               Learning Rate. Default=0.001
+  --step STEP           Sets the learning rate to the initial LR decayed by
+                        momentum every n epochs, Default: n=10
+  --clip CLIP           Clipping Gradients. Default=0.4
+  --weight-decay WEIGHT_DECAY, --wd WEIGHT_DECAY
+                        Weight decay, Default: 1e-4
+  --cuda                use cuda?
+  --threads THREADS     number of threads for data loader to use
+  --gpuids GPUIDS [GPUIDS ...]
+                        GPU ID for using
+  --add_noise           add gaussian noise?
+  --noise_std NOISE_STD
+                        standard deviation of gaussian noise
+  --test                test mode
+  --model PATH          path to test or resume model
+```
+
+#### Example for training
 ```
 > python main.py --dataset DF2K --cuda --gpuids 0 1 --upscale_factor 2 --crop_size 256 --batch_size 128 --test_batch_size 32 --epochs 100
 ```
@@ -22,7 +61,7 @@ or
 > python3 main.py --dataset DF2K --cuda --gpuids 0 1 --upscale_factor 2 --crop_size 256 --batch_size 128 --test_batch_size 32 --epochs 100
 ```
 
-## Test
+### Example for evaluation
 ```
 > python main.py --dataset Urban100 --cuda --gpuids 0 1 --upscale_factor 2 --crop_size 256 --test_batch_size 32 --test --model model_epoch_100.pth
 ```
@@ -31,7 +70,28 @@ or
 > python3 main.py --dataset Urban100 --cuda --gpuids 0 1 --upscale_factor 2 --crop_size 256 --test_batch_size 32 --test --model model_epoch_100.pth
 ```
 
-## Sample usage
+### Sample usage
+```
+usage: run.py [-h] --input_image INPUT_IMAGE --model MODEL
+              [--output_filename OUTPUT_FILENAME]
+              [--scale_factor SCALE_FACTOR] [--cuda]
+              [--gpuids GPUIDS [GPUIDS ...]]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --input_image INPUT_IMAGE
+                        input image to use
+  --model MODEL         model file to use
+  --output_filename OUTPUT_FILENAME
+                        where to save the output image
+  --scale_factor SCALE_FACTOR
+                        factor by which super resolution needed
+  --cuda                use cuda
+  --gpuids GPUIDS [GPUIDS ...]
+                        GPU ID for using
+```
+
+#### Example for demonstration
 ```
 > python run.py --cuda --gpuids 0 1 --scale_factor 2 --model model_epoch_100.pth --input_image test_scale2x.jpg --output_filename test_scale2x_out.jpg
 ```