The PlaNet dataset is being used to detect floating and terra firma waste debris in oceans/ports/harbors/beaches, urban and rural areas allowing the eradication of waste, helping marine life, fishermen, tourism and making the world resilient to climate change by Recyclero.
The dataset has been collected in a joint effort between the Recyclero and the Manipal University Jaipur. Students were able to contribute by sending their pictures of plastics, glass, paper, rubbish, metal and cardboard with our custom-built application.
This repository contains the dataset that we collected. The dataset spans six classes: glass, paper, cardboard, plastic, metal, and trash. Currently, the dataset consists of 2527 images,
- 501 glass
- 594 paper
- 403 cardboard
- 482 plastic
- 410 metal
- 137 trash
The pictures were taken by placing the object on a white posterboard and using sunlight and/or room lighting. The pictures have been resized down to 512 x 384, which can be changed in dataset/constants.py (resizing them involves going through step 1 in usage). The devices used were Apple iPhone 7 Plus, Apple iPhone 5S, and Apple iPhone SE.
If adding more data, then the new files must be enumerated properly and put into the appropriate folder in dataset/original and then preprocessed. Preprocessing the data involves deleting the dataset/resized folder and then calling python resize.py from PlaNet/dataset/*. This will take around half an hour.
Python is currently used for some image preprocessing tasks. The Python dependencies are,
You can install these packages by running the following,
# Install using pip
pip install numpy scipy- Fork the repository
- Create your feature branch using
git checkout -b my-new-feature - Commit your changes using
git commit -m 'Add some feature' - Push to the branch using
git push origin my-new-feature - Submit a pull request