https://github.com/balavenkatesh3322/docker_video_analysis
Video analysis using YoloV3 and openCV library
https://github.com/balavenkatesh3322/docker_video_analysis
computer-vision docker object-detection opencv videoanalysis yolov3
Last synced: 27 days ago
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Video analysis using YoloV3 and openCV library
- Host: GitHub
- URL: https://github.com/balavenkatesh3322/docker_video_analysis
- Owner: balavenkatesh3322
- Created: 2020-03-20T08:11:21.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-04-11T10:45:31.000Z (about 6 years ago)
- Last Synced: 2025-01-06T01:30:55.980Z (over 1 year ago)
- Topics: computer-vision, docker, object-detection, opencv, videoanalysis, yolov3
- Language: Python
- Homepage:
- Size: 5.86 MB
- Stars: 1
- Watchers: 4
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# docker_video_analysis
## Introduction
I have setup docker file to do Video analysis using Yolo and openCV library which will read video as frames and detect objects in that frames. I saved all videos files and output json file in local videos folder.
## Dependencies
Docker image with python 3.7 and opencv 4.1.0
Build and tag the image "sudo docker build -t opencvcalculai ."
Run docker file "sudo docker run -d opencvcalculai:latest"
Run this command "xhost local:root" when erro occures as "Gtk-WARNING **: 06:49:47.946: cannot open display: unix:0"
docker-compose build
docker-compose up
or
Install below required library in your local machine.
1) python 3.7
2) opencv 4.1.0
3) numpy
## Download Pre-Trained Yolov3 Model file
Download the pre-trained YOLO v3 weights file from this [link](https://drive.google.com/file/d/1AECks3mc2Xwe2BjvNdC_QKiiKZF8wt35/view?usp=sharing) and place it in the current directory
## Quick Start
This analyse python file using Yolov3 to detect objects from videos and save object names as JSON file in videos folder.
## Sample Output
I have uploaded sample json file results in videos folder.
{'remote', 'cup', 'cell phone', 'person'}