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Waste Detection in the Wild - Use Instance segmentation model that segments and classifies the litter found in different environments. Deployment is done using StreamlitCloud.

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Name		Name	Last commit message	Last commit date
Latest commit History 128 Commits
.idea		.idea
Colab		Colab
Short Report		Short Report
assets		assets
hide		hide
.gitattributes		.gitattributes
README.md		README.md
img.jpg		img.jpg
main.py		main.py
model_final.pth		model_final.pth
my_metadata		my_metadata
requirements.txt		requirements.txt

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Waste Detection in the Wild

This project was part of ZAKA AI Certification Program 2022. Goal: Detect Litter in Nature by Image Segmentation

Report:

You can find more info in this report: https://github.com/Nabil-Miri/mystreamlit/blob/main/Short%20Report/Milestone%203.pdf

[UPDATE 2023: Currently there is an error, seems like something has changed in streamlit or version of the library]

[Link: https://nabil-miri-mystreamlit-main-jc5p5m.streamlit.app/] (Note: Just wake up the app if it is asleep)

Downlaod Dataset:

Either from here: https://zenodo.org/record/3587843#.Y4xym3bMJPY or from the download.py file in the TACO main repo: https://github.com/pedropro/TACO

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Waste Detection in the Wild - Use Instance segmentation model that segments and classifies the litter found in different environments. Deployment is done using StreamlitCloud.

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