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https://github.com/cricksmaidiene/leafydex
🍃 Code, studies, and explorations on plant leaf diseases and leaf type classifications for UC Berkeley MIDS 207 final project
https://github.com/cricksmaidiene/leafydex
berkeley-ai jupyter-notebook keras-tensorflow leaf-disease-classification machine-learning opencv-python python310 tensorflow2
Last synced: 23 days ago
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🍃 Code, studies, and explorations on plant leaf diseases and leaf type classifications for UC Berkeley MIDS 207 final project
- Host: GitHub
- URL: https://github.com/cricksmaidiene/leafydex
- Owner: cricksmaidiene
- License: bsd-3-clause
- Created: 2022-09-17T17:59:56.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-12-10T17:40:16.000Z (about 2 years ago)
- Last Synced: 2023-06-03T19:22:21.329Z (over 1 year ago)
- Topics: berkeley-ai, jupyter-notebook, keras-tensorflow, leaf-disease-classification, machine-learning, opencv-python, python310, tensorflow2
- Language: Jupyter Notebook
- Homepage:
- Size: 44.3 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Multispecies Leaf Disease & Leaf Type Classification 🍃
**Authors**
[Eshwaran Venkat](mailto:[email protected]) & [Tigran Poladian](mailto:[email protected]) under [Uri Schonfeld](mailto:[email protected])
- [Multispecies Leaf Disease \& Leaf Type Classification 🍃](#multispecies-leaf-disease--leaf-type-classification-)
- [Setup 📦](#setup-)
- [:notebook: Requirements](#notebook-requirements)
- [Local Setup](#local-setup)
- [Use Github Codepsaces](#use-github-codepsaces)
- [Dataset Setup 🛠](#dataset-setup-)
- [Additional guides](#additional-guides)
## Setup 📦
### :notebook: Requirements
- `[email protected]`
- `conda` environment
### Local Setup
Assuming `conda` and `python` are available and are in `PATH` (accessible from anywhere on the system), run the following commands:
```bash
conda env create --name leafydex python=3.10 -y
conda activate leafydex
conda install -c anaconda ipykernel -y
python -m ipykernel install --user --name=leafydex
git clone https://github.com/cricksmaidiene/leafydex
cd leafydex
python -m pip install -r requirements.txt
python -m pip install -e .
```
### Use Github Codepsaces
- Go to the top-right corner of the repository and click `Code`
- Start a [github codespaces](https://docs.github.com/en/codespaces) on the `main` branch
- append `?editor=jupyter` of the codespaces URL to start exploring on Jupyterlab
## Dataset Setup 🛠
> Add Kaggle API key to `/credentials` (all files within this directory are ignored by git)
Instructions for UNIX-based systems (or Codespaces). Windows may require different commands
```bash
mkdir ~/.kaggle #ignore if directory already present
chmod 600 credentials/kaggle.json
cp credentials/kaggle.json ~/.kaggle/kaggle.json
python -m pip install kaggle
kaggle datasets download -d csafrit2/plant-leaves-for-image-classification -p ./data/raw
unzip data/raw/plant-leaves-for-image-classification.zip -d data/raw
rm data/raw/plant-leaves-for-image-classification.zip
```
- Get API key from [`https://www.kaggle.com/account`](https://www.kaggle.com/account)
- Review [Kaggle API Docs](https://www.kaggle.com/docs/api)
## Additional guides
- **Practices**: Please read [practices.md](practices.md) for details on how to set up this project beyond the base installation.
- **Structure**: Please read [structure.md](structure.md) to see the file structure of this project
- **Execution Trail**: Please read [trail.md](trail.md) to see the trail of execution across multiple files
---
Project structure based on the [cookiecutter conda data science project template](https://github.com/jvelezmagic/cookiecutter-conda-data-science).