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Real_Time_Intrusion_Detection_Using_Video_Survelliance

Intro

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

Requirements

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

step-1

Download the Darkflow repo

  • Click this
  • Download and extract the files somewhere locally

Step-2

Build the Darkflow

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 .
    

Step-3

Download a weights file

  • 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

Step-4

Download my repo and copy all the content inside darkflow folder

Step-5

Run the final_product.py

RESULT

See the result video (result.mp4) in my repo. I also added my research paper in this repo. You can follow that.

References

  • 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.