https://github.com/xtalism/object-detection

Object detection with AI using YOLO V8, Opencv and Python 3.8.
https://github.com/xtalism/object-detection

artificial-intelligence computer-vision object-detection python3 yolov8

Last synced: about 1 year ago
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Object detection with AI using YOLO V8, Opencv and Python 3.8.

• Host: GitHub
• URL: https://github.com/xtalism/object-detection
• Owner: Xtalism
• License: mit
• Created: 2024-05-29T00:21:10.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2024-08-06T21:07:02.000Z (almost 2 years ago)
• Last Synced: 2025-04-10T21:09:45.650Z (about 1 year ago)
• Topics: artificial-intelligence, computer-vision, object-detection, python3, yolov8
• Language: Python
• Homepage:
• Size: 1.27 MB
• Stars: 7
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Object Detection

This a Computer Vision "object detection" project. I used Python 3.8 version, yolov8 (you can also use yolov5 if you want) and Opencv to write this program.

In order to install the necessary dependencies we use requirements.txt file and build our Python 3.8 virtual environment. 

Just as follows:

    py -3.8 -m venv {namefyourvirtualenvironment}

    py -m pip -r install requirements.txt

If you happen to change or add new dependencies, you can also make your own requirements.txt file as follows:

    py -m pip freeze --local > requirements.txt

You can make your own AI model with Yolov8 official website which includes a detailed tutorial on how to do it using [Yolov5](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/) or [Yolov8](https://docs.ultralytics.com/). You can also check its proper github [documentation](https://github.com/ultralytics/ultralytics).

If you wish, you can check [Roboflow's](https://blog.roboflow.com/how-to-train-yolov8-on-a-custom-dataset/) documentation also, and explore its open source computer vision datasets and APIs [here](https://universe.roboflow.com/).

![datasets](img/datasets.png)

I personally used a custom dataset [notebook](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/train-yolov8-object-detection-on-custom-dataset.ipynb#scrollTo=oe9vkEvFABbN) from Roboflow.

![notebook](img/notebook.png)