FSDL Deforestation Detection
A deep learning approach to detecting deforestation risk, using satellite images and a deep learning model.
https://github.com/karthikraja95/fsdl_deforestation_detection
Category: Biosphere
Sub Category: Deforestation and Reforestation
Keywords from Contributors
archiving transforms measur generic optimize observation compose conversion projection animals
Last synced: about 23 hours ago
JSON representation
Repository metadata
- Host: GitHub
- URL: https://github.com/karthikraja95/fsdl_deforestation_detection
- Owner: karthikraja95
- License: mit
- Created: 2021-03-29T19:46:39.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2023-01-13T22:01:46.000Z (over 2 years ago)
- Last Synced: 2025-04-17T21:21:01.434Z (11 days ago)
- Language: Jupyter Notebook
- Size: 90.1 MB
- Stars: 39
- Watchers: 3
- Forks: 11
- Open Issues: 10
- Releases: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
README.md
FSDL Deforestation Detection
Detecting deforestation from satellite images: a full stack deep learning project
Description
A deep learning approach to detecting deforestation risk, using satellite images and a deep learning model. We relied on Planet imagery from two Kaggle datasets (one from the Amazon rainforest and another on oil palm plantations in Borneo) and trained a ResNet model using FastAI. For more details, check the following links:
This is the result of a group project, made by André Ferreira and Karthik Bhaskar, for the Full Stack Deep Learning - Spring 2021 online course.
Very first steps
Initial
- Initialize
git
inside your repo:
git init
- If you don't have
Poetry
installed run:
make download-poetry
- Initialize poetry and install
pre-commit
hooks:
make install
- Upload initial code to GitHub (ensure you've run
make install
to usepre-commit
):
git add .
git commit -m ":tada: Initial commit"
git branch -M main
git remote add origin https://github.com/karthikraja95/fsdl_deforestation_detection.git
git push -u origin main
Initial setting up
- Set up Dependabot to ensure you have the latest dependencies.
- Set up Stale bot for automatic issue closing.
Poetry
All manipulations with dependencies are executed through Poetry. If you're new to it, look through the documentation.
Poetry's commands are very intuitive and easy to learn, like:
poetry add numpy
poetry run pytest
poetry build
- etc
Makefile usage
Makefile
contains many functions for fast assembling and convenient work.
make download-poetry
make install
If you do not want to install pre-commit hooks, run the command with the NO_PRE_COMMIT flag:
make install NO_PRE_COMMIT=1
make check-safety
This command launches a Poetry
and Pip
integrity check as well as identifies security issues with Safety
and Bandit
. By default, the build will not crash if any of the items fail. But you can set STRICT=1
for the entire build, or you can configure strictness for each item separately.
make check-safety STRICT=1
or only for safety
:
make check-safety SAFETY_STRICT=1
multiple
make check-safety PIP_STRICT=1 SAFETY_STRICT=1
List of flags for
check-safety
(can be set to1
or0
):STRICT
,POETRY_STRICT
,PIP_STRICT
,SAFETY_STRICT
,BANDIT_STRICT
.
The command is similar to check-safety
but to check the code style, obviously. It uses Black
, Darglint
, Isort
, and Mypy
inside.
make check-style
It may also contain the STRICT
flag.
make check-style STRICT=1
List of flags for
check-style
(can be set to1
or0
):STRICT
,BLACK_STRICT
,DARGLINT_STRICT
,ISORT_STRICT
,MYPY_STRICT
.
Codestyle uses pre-commit
hooks, so ensure you've run make install
before.
make codestyle
make test
make lint
the same as:
make test && make check-safety && make check-style
List of flags for
lint
(can be set to1
or0
):STRICT
,POETRY_STRICT
,PIP_STRICT
,SAFETY_STRICT
,BANDIT_STRICT
,BLACK_STRICT
,DARGLINT_STRICT
,ISORT_STRICT
,MYPY_STRICT
.
make docker
which is equivalent to:
make docker VERSION=latest
More information here.
make clean_docker
or to remove all build
make clean
More information here.
🛡 License
This project is licensed under the terms of the MIT
license. See LICENSE for more details.
📃 Citation
@misc{fsdl_deforestation_detection,
author = {Karthik Bhaskar, Andre Ferreira},
title = {Predicting deforestation from Satellite Images},
year = {2021},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/karthikraja95/fsdl_deforestation_detection}}
}
Owner metadata
- Name: Karthik Bhaskar
- Login: karthikraja95
- Email:
- Kind: user
- Description: M.A.Sc | Deep Learning | Vector Institute | U of T | NLP | Software Engineer
- Website: https://www.kbhaskar.com/
- Location: Toronto
- Twitter:
- Company: University of Toronto
- Icon url: https://avatars.githubusercontent.com/u/40802179?u=90fe684f34f5511019c8ddbd08359441008bc91a&v=4
- Repositories: 35
- Last ynced at: 2024-06-11T15:58:40.500Z
- Profile URL: https://github.com/karthikraja95
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers metadata
Last synced: 6 days ago
Total Commits: 53
Total Committers: 3
Avg Commits per committer: 17.667
Development Distribution Score (DDS): 0.321
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
Name | Commits | |
---|---|---|
André Cristóvão Neves Ferreira | a****f@g****m | 36 |
Karthik Bhaskar | k****k@g****m | 10 |
dependabot[bot] | 4****] | 7 |
Committer domains:
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 0
Total pull requests: 130
Average time to close issues: N/A
Average time to close pull requests: about 1 month
Total issue authors: 0
Total pull request authors: 4
Average comments per issue: 0
Average comments per pull request: 0.83
Merged pull request: 11
Bot issues: 0
Bot pull requests: 121
Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
Top Pull Request Authors
- dependabot[bot] (121)
- cclauss (4)
- AndreCNF (4)
- karthikraja95 (1)
Top Issue Labels
Top Pull Request Labels
- dependencies (121)
- python (68)
- github_actions (53)
Dependencies
- streamlit *
- actions/cache v2.1.4 composite
- actions/checkout v2 composite
- actions/setup-python v2.2.1 composite
- actions/first-interaction v1 composite
- release-drafter/release-drafter v5.15.0 composite
- python 3.7-slim-buster build
Score: 4.990432586778736