COCO Annotation Converter

Description

COCO Annotation Converter is a Python script designed to convert annotations from the pred_coco.json format to the COCO Results Format. This tool is useful for those working with COCO datasets who need to transform predictions into a compatible format for analysis and evaluation.

Features

• Support for Various Annotation Structures: Handles annotations as dictionaries containing the annotations key as well as lists of annotations.
• Confidence Score Filtering: Allows setting a minimum score threshold to include only relevant detections.
• Category Management: Maps category names to their respective IDs based on ground truth annotations.
• Support for Segmentations and Keypoints: Includes segmentation and keypoint information if present in the annotations.

Requirements

• Python 3.6 or higher

Installation

1. Clone the Repository:

   git clone https://github.com/your-username/coco-annotation-converter.git
   cd coco-annotation-converter

2. Create a Virtual Environment (Optional but Recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Dependencies:

   pip install -r requirements.txt

   If the requirements.txt file is not present, you can install dependencies manually:

   pip install argparse

Usage

Run the converter.py script via the command line, specifying the paths to the necessary files.

python converter.py --pred PATH_TO_PRED_COCO_JSON --output OUTPUT_PATH [--score_thresh THRESHOLD]

Or as external pip package as:

import converter
converter.setup_logging()
converter.convert_pred_coco('path/to/pred_coco.json', 'path/to/output.json')