Real-time Traffic and Pedestrian Counting (YOLOV3 in tensorflow2)
This project focuses " counting and statistics of moving targets we care about ", drive by YOLOv3 which was Implemented in Tensorflow2."
It needs to be stated that the YOLOv3 detector of this project is forked from the nice implementation of YunYang1994
Reproduce the environment
conda env create -f environment.yml
wget https://pjreddie.com/media/files/yolov3.weights
two test videos are prepared here, you should download.
video_path = "./vehicle.mp4"
num_classes = 80
utils.load_weights(model, "./yolov3.weights")
conda activate your_env_name
python video_demo.py
If you use this code for your publications, please cite it as:
@ONLINE{vdtc,
author = "Clemente420",
title = "Real-time-Traffic-and-Pedestrian-Counting",
year = "2020",
url = "https://github.com/Clemente420/Real-time-Traffic-and-Pedestrian-Counting"
}
This system is available under the MIT license. See the LICENSE file for more info.