Yolov7-Object-Counter and custom functions

• Object Counting and custom functions with the newest yolov7
• Crop the bounding boxes

Track_Trim.mp4

Ready to use tracking Google Colab file: https://colab.research.google.com/drive/1RK1IgQx6Fr7D2BwgCQJiUiZPclj69Myv?usp=sharing

Update 1 (9/21/2022) a new model added for stock market predicion. Model file:https://drive.google.com/file/d/1_ud8ldVz1mnRU_Z3ygXEm0kWSjgSeOEW/view?usp=sharing

• To detect: "stock_market_detect.py" file
• Example video is below

Update 2 (9/26/2022) a new file added for saving the images of bounding boxes file name: "save_bounding_boxes_images.py"

• Example photo is below

Update 3 (10/17/2022) a new file added for tracking and counting them. File name: "TRACK-SOURCE.py"

videoo.mp4

Please read first "README" before browsing the code

Ready-to-use Google Colab file exists. you can copy this file and run it on your colab. File: https://colab.research.google.com/drive/1Bezq6IpAraT8Ee0v8flEJco6wsLn0T3I?usp=sharing

• There are steps for applying object counter on images and videos

Features

• Count all objetcs by classes and works perfetcly on every image or on a video
• Code can run on Both (CPU & GPU)
• Video/WebCam/External Camera/IP Stream Supported

It is super easy to run

• We are going to copy offical yolov7 github page and just add "detect_and_count.py" file. That is all
• When you use Google Colab for codes, it will be way easier than working on the local computer

Steps to run Code

• clone the repository:
• git clone https://github.com/WongKinYiu/yolov7
• %cd yolov7
• install yolov7 model
• !wget "https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt"

Upgrade pip with mentioned command below.

pip install --upgrade pip

Install requirements with mentioned command below.

pip install -r requirements.txt

Using counter

!python detect_and_count.py --weights /content/yolov7/yolov7.pt --conf 0.1 --source /content/yolov7/inference/images

Results!

Stock market detection video:

Stock.market_Trim.mp4

Saving the images of bounding boxes

References

• https://github.com/WongKinYiu/yolov7