kdncode / tensorFlow-react

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Sample

YOLO v2

YOLO9000 is a high speed, real time detection algorithm that can detect on OVER 9000! (object categories). Read more

Requirements

pip install opencv-python

Download Darkflow repo

Build the library

  • Cd to darkflow-master folder that just extracted.
  • Open terminal & Run:
python setup.py build_ext --inplace

or

pip install -e .

Download the 'weights' file

  • Create bin folder inside darkflow-master folder.
  • Download the YOLOv2 608x608 weights file here.
  • Put the weights file inside bin folder.

Processing video file

  • Put the video into darkflow-master folder.
  • Open terminal & Run:
  • Without GPU version of tensorflow:
python flow --model cfg/yolo.cfg --load bin/yolov2.weights --demo video_file_name.mp4 --saveVideo
  • GPU version of tensorflow:
python flow --model cfg/yolo.cfg --load bin/yolov2.weights --demo video_file_name.mp4 --gpu 1.0 --saveVideo

*NOTE:

  • video_file_name.mp4 changes to your video name.

  • --saveVideo indicates to save a name video file, which has the boxes around objects

License

Darkflow

Video credit

Photo credit

About

ML

License:GNU General Public License v3.0


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Language:Python 100.0%