Spaces:
Configuration error
Configuration error
File size: 3,196 Bytes
41be7ed 72e1bbb 41be7ed 72e1bbb 41be7ed | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 | # Plant Identifier – Hyderabad Locator (Python)
This project lets you:
1. Upload a **plant JPG** photo.
2. Identify the plant using the **Plant.id API** (AI model).
3. Show **where the plant has been observed in Hyderabad** (using the iNaturalist public API) and plot it on an interactive map.
It ships with a **Streamlit UI** (`streamlit_app.py`) so you can run everything locally in a few minutes.
---
## Features
- 📷 Image upload (JPG/JPEG/PNG) via Streamlit
- 🤖 AI recognition via **Plant.id** (top matches with confidence, scientific name, common names, wiki details when available)
- 📍 Hyderabad occurrences via **iNaturalist** (observations plotted on a Folium map)
- 🗺️ Interactive map embedded in the app
- 🔑 `.env` support for secrets
> **Note**: You need a free or paid **Plant.id** API key. Create an account at plant.id and copy your key into `.env` as `PLANT_ID_API_KEY`.
---
## File structure
```
plant-identifier-hyd/
├─ app/
│ ├─ streamlit_app.py # Streamlit UI
│ ├─ plant_id_client.py # Plant.id API client
│ ├─ location.py # Hyderabad bbox + iNaturalist search
│ ├─ utils.py # Helpers (image, env)
│ └─ static/
│ └─ styles.css # Optional extra styles for Streamlit
├─ data/
│ └─ sample_images/ # Put example photos here
├─ tests/
│ └─ test_smoke.py # Minimal smoke test
├─ .env.example # Copy to .env and fill in your API key
├─ requirements.txt
└─ README.md
```
---
## Quickstart
1) **Clone or unzip** this folder.
2) Create a virtual environment (recommended):
```bash
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
```
3) **Install dependencies**:
```bash
pip install -r requirements.txt
```
4) **Set your API key**: copy `.env.example` to `.env` and put your Plant.id key.
5) **Run the app**:
```bash
streamlit run app/streamlit_app.py
```
6) Open the printed local URL in your browser.
---
## How it works
### Plant identification
We send the uploaded image to **Plant.id** (`/v3/identification`) and request the top candidates. We show:
- scientific name
- common names
- confidence score
- a short description if available
### Hyderabad locations
We query **iNaturalist** for recent observations within a Hyderabad bounding box. We then plot markers on a **Folium** map and embed it in Streamlit.
> The map shows where people have reported observing the plant in Hyderabad. This does not guarantee the plant is wild there; it simply shows community observations.
---
## Environment variables
Create a `.env` file in the project root:
```
PLANT_ID_API_KEY=your_plant_id_api_key_here
```
---
## Notes & Limits
- API quotas apply (Plant.id & iNaturalist).
- Identification quality depends on your photo (focus, lighting, background).
- iNaturalist observations depend on community contributions—some plants may have few or no reports in the Hyderabad area.
---
## Testing
```bash
pytest -q
```
---
## License
MIT. For learning and non-commercial demo use. Check Plant.id and iNaturalist terms of service for production use.
|