{"id":15519629,"url":"https://github.com/rmitsch/tale","last_synced_at":"2025-12-18T23:30:25.339Z","repository":{"id":90224628,"uuid":"238942114","full_name":"rmitsch/TALE","owner":"rmitsch","description":"Tool for Annotation of Low-dimensional Embeddings.","archived":false,"fork":false,"pushed_at":"2021-03-05T19:21:18.000Z","size":514,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-12-29T10:44:30.908Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rmitsch.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-02-07T14:21:35.000Z","updated_at":"2021-10-26T15:15:37.000Z","dependencies_parsed_at":null,"dependency_job_id":"8330333f-f86d-46ec-b51a-92e5adb4d807","html_url":"https://github.com/rmitsch/TALE","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/rmitsch%2FTALE","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmitsch%2FTALE/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmitsch%2FTALE/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rmitsch%2FTALE/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rmitsch","download_url":"https://codeload.github.com/rmitsch/TALE/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239697004,"owners_count":19682345,"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":[],"created_at":"2024-10-02T10:22:14.445Z","updated_at":"2025-12-18T23:30:24.949Z","avatar_url":"https://github.com/rmitsch.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TALE - Tool for Annotating of Low-dimensional Embeddings\n\nTALE is a **T**ool for **A**nnotation of **L**ow-dimensional **E**mbeddings. It offers functionality to assess, interprete and rate low-dimensional projections, such as those generated by e.g. t-SNE or UMAP. See [todo - add paper link](www.arxiv.org) for a more complete description. It is written in Python (backend) and Javascript (frontend).\nThis repository contains the [dataset with projection features and user ratings](https://github.com/rmitsch/TALE/blob/master/rated_projection_features.pkl) discussed in the paper.\n\nHead over to https://github.com/rmitsch/TALE-backend and https://github.com/rmitsch/TALE-frontend for the actual source code.\n\nTALE allows to explore the parameter space of low-dimensional projections in the global view:\n![TALE: Global view](https://github.com/rmitsch/TALE/blob/master/doc/tale_global.png)\n\nIndividual projections can be inspected, evaluated and rated in the local view:\n![TALE: Local view](https://github.com/rmitsch/TALE/blob/master/doc/tale_local.png)\n\n## Build Instructions\n\n* Pull source code:\n`git clone --recurse-submodules git@github.com:rmitsch/TALE.git`\n* Build the Docker image:\n`docker build -t tale -f Dockerfile .`\n* Alternatively pull the image from Dockerhub:\n`docker pull rmitsch/tale`\n\n## Generate projections\n\n`docker run -v [host data directory]:/data tale python /TALE-backend/source/generate_data.py [dataset name] [DR kernel name] /data`    \n\n`[dataset name]` can be either \"happiness\" for the UN world happiness study or \"movie\" for the IMDB movie dataset.\n`[DR kernel name]` can be \"UMAP\", \"TSNE\" or \"SVD\".\n\n## Run TALE server\n\n`docker run -p 2484:2484 -v [host data directory]:/data tale python /TALE-backend/source/app.py /TALE-frontend /data [experiment name] [Dropbox OAuth Token]`\n\n`[experiment name]` and `[Dropbox OAuth Token]` are optional and only necessary if you want to hook up TALE to a Dropbox account to automatically store the resulting user ratings in the cloud.\n\n## Use TALE\n\nAccess in your browser via localhost:2484.\n\nNote: By default, TALE attempts to load t-SNE projections for the world happiness dataset, i. e. assumes that projections have been generated with \n`docker run -v [host data directory]:/data tale python /TALE-backend/source/generate_data.py happiness TSNE /data`. If you want to look at another configuration, select it in the dataset and DR kernel dropdowns to the top right and click the load button to their right.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frmitsch%2Ftale","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frmitsch%2Ftale","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frmitsch%2Ftale/lists"}