This is a part of my research work titled Deep Learning based Real Time Crime Detection Using Video Survelliance

Python3, tensorflow 1.0, numpy, opencv 3. Links for installation below:

• Python 3.5 or 3.6, Anaconda
• Tensorflow. I recommend using the tensorflow GPU version. But if you don't have GPU, just go ahead and install the CPU versoin.
  GPUs are more than 100x faster for training and testing neural networks than a CPU. Find more here
• Opencv
• pygame
• bokeh

• Click this
• Download and extract the files somewhere locally

You can choose one of the following three ways to get started with darkflow.

1. Just build the Cython extensions in place. NOTE: If installing this way you will have to use ./flow in the cloned darkflow directory instead of flow as darkflow is not installed globally.

   python3 setup.py build_ext --inplace
   

2. Let pip install darkflow globally in dev mode (still globally accessible, but changes to the code immediately take effect)

   pip install -e .
   

3. Install with pip globally

   pip install .
   

• Download the YOLOv2 608x608 weights file here
• Read more about YOLO (in darknet) and download weight files here. In case the weight file cannot be found, you can check here, which include yolo-full and yolo-tiny of v1.0, tiny-yolo-v1.1 of v1.1 and yolo, tiny-yolo-voc of v2. Owner of this weights is Trieu.
• NOTE: there are other weights files you can try if you like
• create a bin folder within the darkflow-master folder
• put the weights file in the bin folder

• Real-time object detection and classification. Paper: version 1, version 2.

• Simple Online and Realtime Tracking paper

• Official YOLO website.

• I have learned YOLO, how it works from coursera. Also Siraj has a nice tutorial on it.

• The original darkflow repo is this by Trieu.