KO - Hackathon

Participants: Nguyen Mau Trong Hieu - Huynh Ngoc Tan

Docker run: https://www.youtube.com/watch?v=GFRnjtjsfXA

Docker command:

sudo docker pull hieuhthh/kohfinal:third

sudo docker run hieuhthh/kohfinal:third

sudo docker run -it -v /home/hieu/video:/home/DETECT hieuhthh/kohfinal:third

https://drive.google.com/drive/u/0/folders/1eFawVAtl9BKvaz0e2NA-hUv5lBR9xZd9

We have inferred 2 videos:

Demo Video 1: https://youtu.be/FgoyfaOtN_Y

Demo Video 2: https://youtu.be/m7b-2d0ML5o

Demo Video final: https://youtu.be/SqsHjEYXuto

HOW TO USE WITH GIT

Quick Tutorial: https://youtu.be/EL_DgZFHHiI

Open command line

You need to change directory to this folder

pip install -r requirements.txt

Put your video/image(s) into folder DETECT

python detect.py

YOLO FORMAT

CLASSES IN LABELS

0 - BOX

1 - PERSON

2 - FIRE

3 - DOG

4 - CAT

5 - ANOMALY (DROPPED BOX)

If DROPPED BOX is TRACKED, then it will be normal box.

REFERENCE

https://github.com/ultralytics/yolov5

https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_canny/py_canny.html

https://docs.opencv.org/3.4/d9/db0/tutorial_hough_lines.html