Hello trend,
This is Satya Mallick from LearnOpenCV.com.
Today's post is the second prize winner of the recently concluded LearnOpenCV Blog Olympics.
According to recent studies, 8 million tons of plastic are dumped into the ocean every year and it is estimated that by 2050 there will be more plastic in the ocean than fish. We use 481.6 billion plastic bottles every year and only about 9% of plastic are recycled.
In today's post, we will learn some easy to use tools for building an end-to-end plastic bottle detector. The post will educate you on the dataset to use, and how to scrape images from the internet for adding additional images to your dataset. You will also learn how to create a data annotation tool within jupyter notebooks, and finally train a model that detects plastic bottles.
All you need is a Google account to run the Colab notebook.
https://learnopencv.com/plastic-waste-detection-with-deep-learning
And the python code is in the following Colab notebooks
- Image Scraper for data collection
- Model Trainer
Today's post is illustrative, and gives absolute beginners an end-to-end pipeline for object detection. However, it does not go into the theory of object detection, or use a standard framework like PyTorch.
Our course Deep Learning with PyTorch builds a solid foundation for people looking for a career in AI. You will learn a perfect balance of theory and build practical experience through assignments and projects. By taking our course, you also help support the development of the FREE OpenCV library.
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Cheers!
Satya
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