This repository contains code and data for analyzing Ethiopian medical businesses, focusing on extracting and processing data from Telegram channels using object detection with YOLOv5. The project is structured to handle data scraping, object detection, data processing, and serving the processed data via a FastAPI web service.

    Ethiopian_medical_businesses_Analysis/
    ├── .dvc/
    ├── .github/
    ├── data/
    ├── notebooks/
    │ └── EDA.ipynb
    ├── src/
    │ ├── Scrape_scripts/
    │ │ ├── main.py
    │ │ ├── tg_data_scrape.py
    │ │ └── tg_image_scrape.py
    │ ├── model/
    │ │ ├── detect_objects.py
    │ │ ├── handler.py
    │ │ ├── insert_data.py
    │ │ ├── process_results.py
    │ │ └── visualizer.py
    │ ├── transformation/ethio_medical_business/
    ├── analyses/
    ├── macros/
    ├── models/
    ├── seeds/
    │ └── seeds.yml
    ├── snapshots/
    ├── tests/
    ├── web_service/
    ├── .dvcignore
    ├── .gitignore
    ├── README.md
    ├── requirements.txt
    ├── test.db
    ├── yolov5s.pt
    └── dbt_project.yml

Create a virtual environment and install the required dependencies:

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install the necessary packages
pip install -r requirements.txt

git clone https://github.com/ultralytics/yolov5.git
cd yolov5
pip install -r requirements.txt
cd ..

Edit tg_image_scrape.py with your own Telegram API credentials and run the script to download images:

python src/Scrape_scripts/tg_image_scrape.py

Run the detect_objects.py script to detect objects in the downloaded images:

python src/model/detect_objects.py

Run the process_results.py script to process detection results:

python src/model/process_results.py

Run the insert_data.py script to insert the processed data into the database:

python src/model/insert_data.py

Run the FastAPI application to serve the processed data:

uvicorn src/web_service.main:app --reload

Access the API endpoints:

To get detections: http://127.0.0.1:8000/detections/
To create a detection: Use an HTTP client like Postman or cURL to POST data to http://127.0.0.1:8000/detections/.

Scripts for scraping data from Telegram channels:

• src/Scrape_scripts/main.py
• src/Scrape_scripts/tg_data_scrape.py
• src/Scrape_scripts/tg_image_scrape.py

Scripts for detecting objects in images and processing the results:

• src/model/detect_objects.py
• src/model/handler.py
• src/model/insert_data.py
• src/model/process_results.py
• src/model/visualizer.py

Exploratory Data Analysis (EDA):

• notebooks/EDA.ipynb

FastAPI web service for serving the processed data:

• src/web_service/main.py

• test.db: SQLite database file
• dbt_project.yml: DBT project configuration
• seeds.yml: Seeds configuration

This project is licensed under the MIT License. See the LICENSE file for details.