https://github.com/akashkobal/potato-disease-classification
https://github.com/akashkobal/potato-disease-classification
Last synced: 9 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/akashkobal/potato-disease-classification
- Owner: AkashKobal
- License: mit
- Created: 2023-11-20T17:32:11.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-14T06:01:06.000Z (over 2 years ago)
- Last Synced: 2024-12-05T22:10:30.115Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage: https://theakash.co.in
- Size: 44.9 MB
- Stars: 8
- Watchers: 2
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Potato Disease Classification with Deep Learning
This repository implements a deep learning-based solution for accurate classification of potato diseases. Leveraging state-of-the-art convolutional neural networks (CNNs), the model is trained on a comprehensive dataset of potato plant images, encompassing various diseases.
Key Features:
1. Deep Learning Model: Utilizes a robust CNN architecture for high-precision disease classification.
2. Dataset: A curated dataset of diverse potato plant images, annotated with disease labels.
3. Training Pipeline: Clear and reproducible code for model training, including data preprocessing and augmentation.
4. Evaluation Metrics: Detailed analysis of model performance using standard metrics like accuracy, precision, recall, and F1 score.
5. Inference: Deploy the trained model for real-time or batch inference on new potato plant images.
Getting Started:
1. Clone the repository: `git clone https://github.com/AkashKobal/potato-disease-classification`
2. Install dependencies: `pip install -r requirements.txt`
3. Explore the Jupyter notebooks in the `notebooks` directory for model training and evaluation.