PyPicTagger

Description

This Python script automates the process of classifying images. It reads image URLs from a CSV file, classifies them using the Clarifai API, and writes the results to another CSV file. This project showcases skills in API integration, error handling, and file operations in Python.

Features

• Automated Image Tagger: Streamlines the process of tagging the images based on their content.
• API Integration: Utilizes the Clarifai API for advanced image recognition.
• Error Handling: Implements robust error handling and retry strategies for API requests.
• CSV Operations: Reads from and writes to CSV files, enabling easy data manipulation and storage.

Getting Started

Dependencies

• Python 3.x
• clarifai_grpc for API access
• python-dotenv for environment variable management
• backoff for retry logic

Setup

1. Clone this repository.
2. Install dependencies: pip install -r requirements.txt
3. Create a .env file with your Clarifai API key: API_KEY=<Your_API_Key>

Usage

1. Prepare a CSV with image URLs in the first column.
2. Execute the script: python pypic.py
3. View results in classified_images.csv, including tags and confidence scores.

Project Structure

• pypic.py: The main script that orchestrates the classification process.
• .env: An .env file.
• requirements.txt: Lists all the project dependencies.

Contributing

We welcome contributions! If you're interested in improving this project, check the issues page for open tasks. To contribute:

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/AmazingFeature).
3. Commit your changes (git commit -m 'Add some AmazingFeature').
4. Push to the branch (git push origin feature/AmazingFeature).
5. Open a Pull Request.