https://github.com/m-rishab/cropcare
A solution for intelligent and simplified agriculture.
https://github.com/m-rishab/cropcare
cnn deeplearning flask kaggle-dataset python3 pytorch resnet-50 tensorflow weather-api
Last synced: 2 months ago
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A solution for intelligent and simplified agriculture.
- Host: GitHub
- URL: https://github.com/m-rishab/cropcare
- Owner: m-rishab
- License: apache-2.0
- Created: 2023-11-25T07:07:23.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-12T07:04:04.000Z (over 2 years ago)
- Last Synced: 2025-07-31T01:17:43.342Z (11 months ago)
- Topics: cnn, deeplearning, flask, kaggle-dataset, python3, pytorch, resnet-50, tensorflow, weather-api
- Language: Jupyter Notebook
- Homepage:
- Size: 9.65 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CropCare Project
CropCare is an innovative agricultural project designed to address critical challenges in modern farming. Leveraging advanced technologies for precision farming, the system comprises three essential components: Crop Recommendation, Fertilizer Recommendation, and Plant Disease Detection. The primary objective is to empower farmers with data-driven insights and smart solutions to optimize crop yield, reduce resource wastage, and enhance overall farm productivity.
## Components
1. **Crop Recommendation:** Provides personalized recommendations for suitable crops based on various factors, aiding farmers in making informed planting decisions.
2. **Fertilizer Recommendation:** Offers precise recommendations for fertilizers tailored to the specific needs of crops, ensuring efficient resource utilization.
3. **Plant Disease Detection:** Utilizes advanced technology to identify and diagnose plant diseases, enabling early intervention and minimizing crop damage.
## Data Flow Diagram

## System Design
### Crop Recommendation

### Fertilizer Recommendation

### Plant Disease Detection

## Test Dataset (For Plant Disease)
[https://drive.google.com/drive/folders/1z_S7CJ80B3NKQ35hwfNLCNWfrXFX4cyK?usp=sharing]
## OpenWeatherMap API Integration

## Demo
## *DEMO-1 ( Crop Recommendation)*

## *DEMO-2 ( Fertilier Recommendation)*

# *DEMO-3 (Plant-Disease Detection & Classification)*

## How to Run
To run the code, use the following command:
```bash
python app.py
or
flask run