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https://github.com/thecoderpinar/plant-health-monitoring
🌱 This project aims to automate plant health monitoring using computer vision and deep learning. It focuses on accurate disease detection and classification in plants through rigorous data preprocessing and robust model selection.
https://github.com/thecoderpinar/plant-health-monitoring
agriculture artificial-intelligence cnn cnn-model computer-vision deep-learning github keras machine-learning open-source opencv plant-health tensorflow
Last synced: 25 days ago
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🌱 This project aims to automate plant health monitoring using computer vision and deep learning. It focuses on accurate disease detection and classification in plants through rigorous data preprocessing and robust model selection.
- Host: GitHub
- URL: https://github.com/thecoderpinar/plant-health-monitoring
- Owner: ThecoderPinar
- License: mit
- Created: 2023-11-06T15:16:28.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-07T15:48:40.000Z (about 1 year ago)
- Last Synced: 2024-01-29T09:19:16.469Z (12 months ago)
- Topics: agriculture, artificial-intelligence, cnn, cnn-model, computer-vision, deep-learning, github, keras, machine-learning, open-source, opencv, plant-health, tensorflow
- Language: Jupyter Notebook
- Homepage: https://www.kaggle.com/competitions/plant-pathology-2020-fgvc7
- Size: 14.5 MB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Plant Health Monitoring Project
## 🏡 About The Project
This project aims to create an automated system for monitoring plant health using computer vision techniques. It leverages deep learning models for disease detection and classification in plants.
## 🚀 Project Highlights
- **Data Preprocessing:** Handling missing values and outliers
- **Feature Scaling:** Applying normalization and standardization for improved performance
- **Model Selection:** Testing various algorithms to identify the best-performing model
- **Data Visualization:** Creating insightful visualizations for better understanding
- **Model Evaluation:** Assessing model performance using various metrics
## 📊 Project Details
### Data Set Description
The dataset comprises various features related to plant health, including images, environmental factors, and other relevant attributes. It encompasses a diverse range of plant diseases and related information.
### Project Steps
1. **Data Exploration and Preprocessing:**
- Identifying and handling missing values and anomalies
- Augmenting the dataset to increase its size and diversity
2. **Model Building and Evaluation:**
- Implementing deep learning models for disease classification
- Evaluating model performance and selecting the most accurate model
3. **Data Visualization:**
- Visualizing image data and disease distribution
- Analyzing patterns and correlations in the dataset
## 🛠️ Technologies Used
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- TensorFlow
## 📋 Installation
1. Clone the repository
```sh
git clone https://github.com/ThecoderPinar/Plant-Health-Monitoring-Project.git
2. Install required packages
```sh
pip install -r requirements.txt
## 🤝 Contributing
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
**Fork the Project**
- Create your Feature Branch (git checkout -b feature/Plant-Health-Monitoring-Project)
- Commit your Changes (git commit -m 'Add some Plant-Health-Monitoring-Project')
- Push to the Branch (git push origin feature/Plant-Health-Monitoring-Project)
- Open a Pull Request
## 📝 License
Distributed under the MIT License. See LICENSE for more information.