Streamlit tool to explore coco datasets

Last update: Dec 16, 2022

Overview

What is this

This tool given a COCO annotations file and COCO predictions file will let you explore your dataset, visualize results and calculate important metrics.

Running the explorer on example data

You can use the predictions I prepared and explore the results on the COCO validation dataset. The predictions are coming from a Mask R-CNN model trained with mmdetection.

Download (and extract in project directory) the labels, annotations and images:

https://drive.google.com/open?id=1wxIagenNdCt_qphEe8gZYK7H2_to9QXl

Setup using docker

sudo docker run -p 8501:8501 -it -v "$PWD"/coco_data:/coco_data i008/cocoexp:latest  \
    --coco_train /coco_data/ground_truth_annotations.json \
    --coco_predictions /coco_data/predictions.json  \
    --images_path /coco_data/images/

Setup using conda

conda env update
conda activate cocoexplorer
streamlit run coco_explorer.py -- --coco_train ./coco_data/ground_truth_annotations.json --coco_predictions ./coco_data/predictions.json  --images_path ./coco_data/val2017/

Setup using pip

python3 -m venv .venv
. .venv/bin/activate
pip install -r requirements.txt
streamlit run coco_explorer.py -- --coco_train ./coco_data/ground_truth_annotations.json --coco_predictions ./coco_data/predictions.json  --images_path ./coco_data/val2017/

go to http://localhost:8501

Running on your own data

In the same way you can explore your own results. Just follow the official COCO dataset format for annotations and predictions.

Streamlit tool to explore coco datasets

Related tags

Overview

What is this

Running the explorer on example data

Running on your own data

Examples

Owner

Jakub Cieslik

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