{"id":42571053,"url":"https://github.com/nexuist/seev","last_synced_at":"2026-01-28T21:08:30.918Z","repository":{"id":197795369,"uuid":"699424264","full_name":"Nexuist/seeV","owner":"Nexuist","description":"A macOS command line wrapper around the Apple Vision framework","archived":false,"fork":false,"pushed_at":"2025-11-23T08:25:46.000Z","size":91236,"stargazers_count":32,"open_issues_count":4,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-11-23T10:13:13.754Z","etag":null,"topics":["cli","computer-vision","machine-learning","macos"],"latest_commit_sha":null,"homepage":"","language":"Swift","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/Nexuist.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-10-02T15:52:40.000Z","updated_at":"2025-11-23T08:25:50.000Z","dependencies_parsed_at":"2024-05-30T01:30:15.648Z","dependency_job_id":null,"html_url":"https://github.com/Nexuist/seeV","commit_stats":{"total_commits":6,"total_committers":1,"mean_commits":6.0,"dds":0.0,"last_synced_commit":"37a0a6e3e313b7d71d60b93ca64e416b0e4f2037"},"previous_names":["nexuist/seev"],"tags_count":4,"template":false,"template_full_name":null,"purl":"pkg:github/Nexuist/seeV","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nexuist%2FseeV","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nexuist%2FseeV/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nexuist%2FseeV/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nexuist%2FseeV/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Nexuist","download_url":"https://codeload.github.com/Nexuist/seeV/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nexuist%2FseeV/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28851838,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-28T15:15:36.453Z","status":"ssl_error","status_checked_at":"2026-01-28T15:15:13.020Z","response_time":57,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["cli","computer-vision","machine-learning","macos"],"created_at":"2026-01-28T21:08:30.335Z","updated_at":"2026-01-28T21:08:30.910Z","avatar_url":"https://github.com/Nexuist.png","language":"Swift","funding_links":[],"categories":[],"sub_categories":[],"readme":"# seeV\n\nseeV is a macOS command line wrapper around the [Apple Vision framework](https://developer.apple.com/documentation/vision). Its goal is to unlock the functionality of the framework for use in shell scripts and other command line tools. seeV is written in Swift and works on macOS 10.14 and later.\n\nBecause Vision.framework ships on macOS, seeV does not require any additional dependencies or network access. It is a single executable that can be copied to any location on your system.\n\n## Supported Operations\n\n### Subject Extraction\n\n![Subject demo](assets/demos/subject.png)\n\n```sh\nseev input.jpg -o output.png\n```\n\n* On a 2020 M1 MacBook Air subject extraction completes in under one second\n* Image can be output to a specified file or stdout\n\n### Face Detection\n\n![Face demo](assets/demos/faces.png)\n\n```sh\nseev faces input.jpg -o output.png\n```\n\n* Results are output in JSON and include the bounding box of each detected face\n* Red bounding boxes can be drawn around each face\n* Output can be cropped to just the face\n\n### Human Detection\n\n![Human demo](assets/demos/humans.png)\n\n```sh\nseev humans input.jpg -o output.png\n```\n\n* Results are output in JSON and include the bounding box of each detected human\n* Only the upper body needs to be visible for detection (does not require full body)\n* Red bounding boxes can be drawn around each human\n\n### Pose Detection\n\n![Pose demo](assets/poses/output.png)\n\n```sh\nseev poses input.jpg -o output.png\n```\n\n* Requires macOS 11 or later\n* Results are output in JSON and include the joints with x/y coordinates and confidence\n* Joint locations and limb connections are drawn to the output image when `-o` is provided\n\n### Text Detection (OCR)\n\n![Text demo](assets/demos/text.png)\n\n```sh\nseev text input.jpg -o output.png\n```\n\n* Results are output in JSON and include the bounding box of each detected phrase\n* Red bounding boxes can be drawn around each phrase\n* Custom words to identify can be provided as a command line argument\n\n### Embeddings\n\n![Embeddings demo](assets/demos/embeddings.png)\n\n```sh\nseev embeddings input.jpg\n```\n\n```sh\nseev distance input.jpg -o comparison.png\n```\n\n* Embeddings are provided as a JSON object and include an array of floating point numbers\n  * See [example](assets/embeddings/steve.json)\n* Embeddings can be used to quantitatively assess image similarity\n\n### Image Distance\n\n![Distance demo](assets/demos/distance.png)\n\n```sh\nseev distance input.jpg -o comparison.png\n```\n\n* Calculates distance between images e.g. how similar are two images\n* Automatically generates embeddings and compares using cosine similarity\n* Distance is a floating point number between 0 and 1\n* Lower distance means images are more similar\n\n## Installation\n\n### Release\n\nYou can download the latest M1 build from the [Releases]( https://github.com/Nexuist/seeV/releases) page.\n\n### Build from Source\n\n```bash\nswift build --configuration release\ncp -f .build/release/seev /usr/local/bin/seev\n```\n\n## Development\n\n```sh\nswift run seev \u003carguments\u003e\n```\n\n* Don't forget to increment the version number in `seev.swift`\n\n## Next Steps\n\n* Determine which Vision.framework features to support next (pose detection, animals, etc)\n* Provide feedback and development direction in [this issue](https://github.com/Nexuist/seeV/issues/7)\n\n## License\n\n```text\nMIT License\n\nCopyright (c) 2024 Andi Andreas\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnexuist%2Fseev","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnexuist%2Fseev","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnexuist%2Fseev/lists"}