{"id":20009923,"url":"https://github.com/i008/coco-dataset-explorer","last_synced_at":"2025-05-04T19:36:00.955Z","repository":{"id":44380988,"uuid":"258148560","full_name":"i008/COCO-dataset-explorer","owner":"i008","description":"Streamlit tool to explore coco datasets","archived":false,"fork":false,"pushed_at":"2022-04-13T19:06:39.000Z","size":9328,"stargazers_count":88,"open_issues_count":7,"forks_count":14,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-08T11:38:03.788Z","etag":null,"topics":["coco-datasets","instance-segmentation","object-detection","streamlit"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/i008.png","metadata":{"files":{"readme":"README.MD","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-04-23T09:02:23.000Z","updated_at":"2025-02-11T14:21:30.000Z","dependencies_parsed_at":"2022-07-14T13:00:50.344Z","dependency_job_id":null,"html_url":"https://github.com/i008/COCO-dataset-explorer","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i008%2FCOCO-dataset-explorer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i008%2FCOCO-dataset-explorer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i008%2FCOCO-dataset-explorer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i008%2FCOCO-dataset-explorer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/i008","download_url":"https://codeload.github.com/i008/COCO-dataset-explorer/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252390764,"owners_count":21740383,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["coco-datasets","instance-segmentation","object-detection","streamlit"],"created_at":"2024-11-13T07:17:31.063Z","updated_at":"2025-05-04T19:35:57.246Z","avatar_url":"https://github.com/i008.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Dear visitor,\nIf you think about using this software - there are better alternatives out there that do the same (and much much more) and are actively maintained.\nI recommend you to check out fiftyone:\n- https://voxel51.com/docs/fiftyone/\n\n\n### What is this\n\nThis tool given a COCO annotations file and COCO predictions file will let you explore your dataset, visualize results\nand calculate important metrics.\n\n\n### Running the explorer on example data \n\nYou can use the predictions I prepared and explore the results on the COCO validation dataset.\nThe predictions are coming from a Mask R-CNN model trained with mmdetection.\n\n1. Download (and extract in project directory) the labels, annotations and images:\n\nhttps://drive.google.com/open?id=1wxIagenNdCt_qphEe8gZYK7H2_to9QXl\n\n2. Setup using docker\n\n```sh\nsudo docker run -p 8501:8501 -it -v \"$PWD\"/coco_data:/coco_data i008/cocoexp:latest  \\\n    --coco_train /coco_data/ground_truth_annotations.json \\\n    --coco_predictions /coco_data/predictions.json  \\\n    --images_path /coco_data/images/\n```\n\n2. Setup using conda\n```sh\nconda env update\nconda activate cocoexplorer\nstreamlit run coco_explorer.py -- --coco_train ./coco_data/ground_truth_annotations.json --coco_predictions ./coco_data/predictions.json  --images_path ./coco_data/val2017/\n```\n\n2. Setup using pip\n\n```sh\npython3 -m venv .venv\n. .venv/bin/activate\npip install -r requirements.txt\nstreamlit run coco_explorer.py -- --coco_train ./coco_data/ground_truth_annotations.json --coco_predictions ./coco_data/predictions.json  --images_path ./coco_data/val2017/\n```\n\n3. go to http://localhost:8501\n\n\n### Running on your own data\n\nIn the same way you can explore your own results. Just follow the official COCO dataset format for annotations and predictions.\n\n\n### Examples\n\n![alt text](./static/demo1.png \"Logo Title Text 1\")\n\n\n\n\n\n![alt text](./static/demo2.png \"Logo Title Text 1\")\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fi008%2Fcoco-dataset-explorer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fi008%2Fcoco-dataset-explorer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fi008%2Fcoco-dataset-explorer/lists"}