README.md

---
title: Soil Classification Backend
emoji: 🌱
colorFrom: green
colorTo: yellow
sdk: docker
app_port: 7860
pinned: false
license: mit
tags:
  - soil-classification
  - cnn
  - fastapi
  - agriculture
  - tensorflow
  - crop-recommendation
short_description: Classify soil types from images and get crop recommendations
---

# 🌱 Soil Classification Backend

AI-powered **soil image classifier** built with **FastAPI + TensorFlow**. Upload a photo of soil and instantly receive:

- 🏷️ **Soil type** — one of **Black · Clayey · Loamy · Red · Sandy**
- 🌾 **Crop recommendations** — sourced from 8 000+ soil-to-crop mappings
- 🌐 **Multilingual explanations** — English, Hindi, and Odia

---

## 🔌 API

### `POST /api/classify`

**Request**

```json
{
  "imageBase64": "data:image/jpeg;base64,...",
  "language": "English"
}
```

**Response**

```json
{
  "soilType": "Sandy",
  "explanation": "This soil appears to be Sandy soil...",
  "recommendedCrops": ["Barley", "Maize", "Millets"]
}
```

### `GET /`

Health check — returns model status and supported soil classes.

---

## 🧠 Model

| | |
|---|---|
| **Architecture** | CNN (Convolutional Neural Network) |
| **Framework** | TensorFlow / Keras 2.16 |
| **Input** | 224 × 224 RGB image |
| **Classes** | Black, Clayey, Loamy, Red, Sandy |

---

## 🛠️ Stack

| | |
|---|---|
| Web Framework | FastAPI |
| ML | TensorFlow 2.16 (CPU) |
| Image Processing | Pillow |
| Data | pandas + CSV (8 000+ crop mappings) |
| Server | Uvicorn |
| Container | Docker |

---

## 📂 Files

```
├── app.py               # FastAPI app + CNN inference
├── Dockerfile            # Docker build
├── requirements.txt      # Python deps
├── model/
│   └── soil_model007.keras
└── data/
    └── data_core.csv     # Soil → Crop mapping
```

---

## 🌍 Languages Supported

| Language | Code |
|---|---|
| English | `"English"` |
| Hindi | `"Hindi"` |
| Odia | `"Odia"` |

---

<p align="center">
  Made with ❤️ for Indian agriculture · NIELIT Internship
</p>