A3: People counter

The main goal of the project is to count people on the streets. So all parameters are adjusted for the task.

Quick Start

1. Clone repository.
2. Download converted weights of yolo.h5 model file with tf-1.4.0/ Put them into model_data folder.
3. Install requirements.
4. Specify path to input fileRun model with cmd :

   python demo.py --videofile="path/to/your/videofile/" --out_root_dir="path/to/outptu/dir/"
   

Dependencies

The code is compatible with Python 3. The following dependencies are needed to run the tracker:

NumPy
sklean
OpenCV
Pillow
Keras

Additionally, feature generation requires TensorFlow-1.4.0.

Run for other classes

Be careful that the code ignores everything but person. Change class if you want run for other instance:

[A3/yolo3/yolo.py]:

      if predicted_class != 'person': 
           continue 

Notes for future work

You can use any Detector you like to replace Keras_version YOLO to get bboxes , for it is to slow !

Model file model_data/mars-small128.pb need by deep_sort had convert to tensorflow-1.4.0

This work mainly based on https://github.com/Qidian213/deep_sort_yolov3. Thanks a lot guy.