Bulk Image Description

Bulk Image Description is a Python project that automates the process of generating alt text and descriptions for images in bulk using AI-powered image recognition and natural language processing.

Features

• Extracts image URLs from CSV files containing artwork data
• Downloads and resizes images for processing
• Generates alt text and descriptions for images using OpenAI's GPT-4 Vision model
• Supports multiple AI engines (e.g., OpenAI, Claude) and prompt versions
• Modular and extensible design for easy integration with different organizations and AI engines

Directory Structure

Bulk Image Description/

• codebase/ : Contains the main Python files for the project.

  • main.py : The entry point of the program.
  • claude_csv_processor.py : Handles CSV file processing and coordinates the image description generation for OpenAI.
  • openai_csv_processor.py : Handles CSV file processing and coordinates the image description generation for Anthropic Claude.
  • orgs/ : Contains organization-specific image scraping modules.
    • cma_image_utils.py : Cleveland Museum of Art
    • gok_image_utils.py : Georgia O'Keeffe Museum
    • lacma_image_utils.py : LACMA
    • met_image_utils.py : The Met
    • nga_image_utils.py : National Gallery of Art
  • openai_utils.py : Handles interactions with the OpenAI API.
  • claude_utils.py : Handles interactions with the Anthropic Claude API.
  • image_processing.py : Provides functions for downloading and resizing images.
  • config.py : Stores configuration settings for the project.
  • prompt_library.py : Contains prompts for generating descriptions.

• your_org/ : Each organization has its own directory( e.g., cma/, gok/, lacma/, met/, nga/, ...

  • Source CSVs/ : Contains the input CSV files with artwork data.
  • Result CSVs/ : Stores the generated CSV files with alt text and descriptions.
  • Source Images/ : Stores the downloaded source images.
  • Resized Images/ : Stores the resized images.

Installation

1. Clone the repository: git clone https://github.com/your-username/bulk-image-description.git
2. Install the required dependencies: pip install -r requirements.txt
3. Set up the API keys and configurations:
   • Open config.py and update the openai_config dictionary with your OpenAI / Anthropic API key and other settings.
4. Prepare the input CSV files:
   • Place the CSV files containing artwork data in the respective organization's "Source CSVs" directory (e.g., CMA/Source CSVs/).
   • Ensure that the CSV files have a columns named "Name", "Obj URL" containing the Names and URLs of the artwork pages.

Usage and Execution

To generate alt text and descriptions for images, run the following command: python codebase/main.py -org -ai <ai_name> [-images] <input_csv_filename>

• <organization>: The name of the organization (e.g., nga).
• <ai_name>: The name of the AI engine to use (e.g., openai, claude).
• -images (optional): Flag to download and resize images. If not provided, only alt text and descriptions will be generated.
• <input_csv_filename>: The filename of the input CSV file (assumed to be in the organization's "Source CSVs" directory).

Example: python codebase/main.py -org nga -ai openai -images nga_example.csv

The generated alt text and descriptions will be saved in a new CSV file in the organization's "Result CSVs" directory, with the filename format: <input_csv_filename>_<ai_name>_<prompt_version>_<timestamp>.csv.##

Customization and Extension

• To add support for a new organization:

  1. Create a new <organization>_image_utils.py file in the codebase/orgs/ directory.
  2. Implement the extract_image_url function in the new file to extract the image URL from the organization's artwork page.
  3. Create a new root level ORG directory with a Source CSVs directory.

• To add support for a new AI engine:

  1. Create a new <ai_name>_utils.py file in the codebase/ directory.
  2. Implement the necessary functions (e.g., call_ai_assistant, parse_response) in the new file to interact with the AI engine's API.
  3. Create a new <ai_name>_csv_processor.py file in the codebase/ directory, following the structure of existing CSV processor files.
  4. Update the config.py file to include the configuration for the new AI engine.

• To add or modify prompts:

  • Open the prompt_library.py file and add or modify prompts in the specified format.
  • Update the openai_config['prompt_version'] or claude_config['prompt_version'] value in the config.py file to use the desired prompt version.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.