Add README

README.md

@@ -0,0 +1,83 @@
+# DMPR-PS
+
+This is the implementation of DMPR-PS using PyTorch.
+
+## Requirements
+
+* CUDA
+* PyTorch
+* OpenCV
+* NumPy
+* Pillow
+* Visdom (optional)
+* Matplotlib (optional)
+
+## Pre-trained weights
+
+The [pre-trained weights](https://drive.google.com/open?id=1OuyF8bGttA11-CKJ4Mj3dYAl5q4NL5IT) could be used to reproduce the number in the paper.
+
+## Inference
+
+* Image inference
+
+    ```(shell)
+    python inference.py --mode image --detector_weights $DETECTOR_WEIGHTS
+    ```
+
+* Video inference
+
+    ```(shell)
+    python inference.py --mode video --detector_weights $DETECTOR_WEIGHTS --video $VIDEO
+    ```
+
+    `DETECTOR_WEIGHTS` is the trained weights of detector.  
+    `VIDEO` is path to the video.  
+    View `config.py` for more argument details.
+
+## Prepare data
+
+1. Download ps2.0 from [here](https://cslinzhang.github.io/deepps/), and extract.
+2. Download the [labels](https://drive.google.com/open?id=1o6yXxc3RjIs6r01LtwMS_zH91Tk9BFRB), and extract.
+3. Perform data preparation and augmentation:
+
+    ```(shell)
+    python prepare_dataset.py --dataset trainval --label_directory $LABEL_DIRECTORY --image_directory $IMAGE_DIRECTORY --output_directory $OUTPUT_DIRECTORY
+    python prepare_dataset.py --dataset test --label_directory $LABEL_DIRECTORY --image_directory $IMAGE_DIRECTORY --output_directory $OUTPUT_DIRECTORY
+    ```
+
+    `LABEL_DIRECTORY` is the directory containing json labels.  
+    `IMAGE_DIRECTORY` is the directory containing jpg images.  
+    `OUTPUT_DIRECTORY` is the directory where output images and labels are.  
+    View `prepare_dataset.py` for more argument details.
+
+## Train
+
+```(shell)
+python train.py --dataset_directory $TRAIN_DIRECTORY
+```
+
+`TRAIN_DIRECTORY` is the train directory generated in data preparation.  
+View `config.py` for more argument details (batch size, learning rate, etc).
+
+## Evaluate
+
+* Evaluate directional marking-point detection
+
+    ```(shell)
+    python evaluate.py --dataset_directory $TEST_DIRECTORY --detector_weights $DETECTOR_WEIGHTS
+    ```
+
+    `TEST_DIRECTORY` is the test directory generated in data preparation.  
+    `DETECTOR_WEIGHTS` is the trained weights of detector.  
+    View `config.py` for more argument details (batch size, learning rate, etc).
+
+* Evaluate parking-slot detection
+
+    ```(shell)
+    python evaluate.py --label_directory $LABEL_DIRECTORY --image_directory $IMAGE_DIRECTORY --detector_weights $DETECTOR_WEIGHTS
+    ```
+
+    `LABEL_DIRECTORY` is the directory containing testing json labels.  
+    `IMAGE_DIRECTORY` is the directory containing testing jpg images.  
+    `DETECTOR_WEIGHTS` is the trained weights of detector.  
+    View `config.py` for more argument details.

config.py

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 """Configurate arguments."""
 import argparse
 
-# TODO: reproduce all number
+# Threholds are collected by `collect_thresholds.py`.
 
 INPUT_IMAGE_SIZE = 512
 # 0: confidence, 1: point_shape, 2: offset_x, 3: offset_y, 4: cos(direction),