add docker file and edit the README (#77)

README.md

@@ -28,6 +28,18 @@ Usage:
 python demo.py --input-video path/to/your/input/video --weights path/to/model/weights
                --output-format video --output-root path/to/output/root
 ```
+
+## docker demo example
+```bash
+docker build -t towards-realtime-mot docker/
+
+docker run --rm --gpus all -v $(pwd)/:/Towards-Realtime-MOT -ti towards-realtime-mot /bin/bash
+cd /Towards-Realtime-MOT;
+python demo.py --input-video path/to/your/input/video --weights path/to/model/weights
+               --output-format video --output-root path/to/output/root
+
+```
+
 ## Dataset zoo
 Please see [DATASET_ZOO.md](https://github.com/Zhongdao/Towards-Realtime-MOT/blob/master/DATASET_ZOO.md) for detailed description of the training/evaluation datasets.
 ## Pretrained model and baseline models

docker/Dockerfile

@@ -0,0 +1,5 @@
+FROM  pytorch/pytorch:1.3-cuda10.1-cudnn7-devel
+
+RUN apt update && apt install -y ffmpeg libsm6 libxrender-dev
+RUN pip install Cython
+RUN pip install opencv-python cython_bbox motmetrics numba matplotlib sklearn

models.py

@@ -5,12 +5,15 @@ import torch.nn as nn
 
 from utils.parse_config import *
 from utils.utils import *
-from utils.syncbn import SyncBN
 import time
 import math
 
+try:
+    from utils.syncbn import SyncBN
     batch_norm=SyncBN #nn.BatchNorm2d
-#batch_norm=nn.BatchNorm2d
+except ImportError:
+    batch_norm=nn.BatchNorm2d
+
 def create_modules(module_defs):
     """
     Constructs module list of layer blocks from module configuration in module_defs