endofactory 0.1.0

Revolutionary EndoVQA dataset construction tool for rapid dataset mixing and configuration

EndoFactory 🏭

Revolutionary tool for constructing EndoVQA datasets through YAML configuration.

Quick Start

1. Installation

git clone <repository-url>
cd EndoFactory
poetry install

2. Generate Test Data

poetry run python tests/test_data_generator.py

3. Create Configuration

poetry run python -m endofactory.cli create-config --output config.yaml

4. Edit Configuration

datasets:
  - name: endoscopy_vqa_v1
    image_path: /path/to/images
    parquet_path: /path/to/metadata.parquet
    weight: 0.6
  - name: medical_vqa_v2
    image_path: /path/to/images2
    parquet_path: /path/to/metadata2.parquet
    weight: 0.4

columns:
  - uuid
  - question
  - answer
  - options
  - task
  - category

task_proportions:
  task_proportions:
    classification: 0.5
    detection: 0.3
    segmentation: 0.2

export:
  output_path: /path/to/output
  format: parquet

5. Build Dataset

poetry run python -m endofactory.cli build config.yaml --verbose

6. View Results

poetry run python -m endofactory.cli view output/endovqa_dataset.parquet

CLI Commands

create-config

Generate example configuration file

endofactory create-config [--output CONFIG_PATH]

build

Build mixed dataset from configuration

endofactory build CONFIG_PATH [--verbose]

stats

Show dataset statistics

endofactory stats CONFIG_PATH

view

Visualize parquet file structure and data

endofactory view PARQUET_FILE [--rows N] [--columns]

Configuration Options

Dataset Weights

Control proportion of each dataset in final mix:

datasets:
  - name: dataset_a
    weight: 0.7  # 70% from dataset_a
  - name: dataset_b  
    weight: 0.3  # 30% from dataset_b

Task Proportions

Control distribution of different task types:

task_proportions:
  task_proportions:
    classification: 0.4
    detection: 0.4
    segmentation: 0.2
  subtask_proportions:
    classification:
      organ_classification: 0.6
      disease_classification: 0.4

Global Columns

Specify columns to extract (missing columns filled with null):

columns:
  - uuid
  - question
  - answer
  - task

Features

• 🚀 Fast Dataset Mixing: YAML-based configuration for dataset blending
• 📊 Task Proportion Control: Precise control over task/subtask distribution
• 💾 Multiple Export Formats: Support for Parquet and JSONL output
• 🔍 Data Visualization: One-command parquet file inspection
• 🛡️ Schema Flexibility: Automatic handling of different column structures
• ⚡ High Performance: Polars-powered data processing
• 🎯 Reproducible: Configurable random seeds

Project Structure

EndoFactory/
├── src/endofactory/
│   ├── __init__.py
│   ├── cli.py
│   ├── config.py
│   ├── core.py
│   └── yaml_loader.py
├── tests/
├── assets/
├── example_config.yaml
└── pyproject.toml

Requirements

• Python >= 3.9
• Poetry (recommended) or pip

License

MIT License