object-detection-app
The Object Detection App is a web application designed to detect objects in real-time using a webcam or through uploaded images. Additionally, the app allows users to set specific objects for alerts, notifying them when a set object is detected or deleted
What XERJ indexed
Snapshot
The whole repository at commit b519d0a5f6 (2026-10-24). dev is 2 commits ahead.
Selected work
“integrate YOLO26s object detection model using LiteRT-JS WebAss…”. 13 files, 785 lines in utils, components, the project root.
Licence
The repository
LICENSE file checked at the pinned commit; the author agreed to inclusion.
The XERJ corpus
The author agreed by email on 2026-10-25. Same terms as the repository. Answers name the repo, the commit and the file:line.
selected for the XERJ Corpus Hublicence clearedsuggested use: adapt with attribution
reactjstailwindcsstensorflowtypescript
Example questions
- How does object-detection-app implement reactjs?
- What does utils do in object-detection-app?
- Show the tailwindcss code in object-detection-app.
Inside the indexed corpus
- 31 files, 12.5 MB in total, about 413.9 KB per file.
- The selected commit changed 13 of those files (41.9%).
- Languages by size: TypeScript 95.2%, JavaScript 3.3%, CSS 1.6%.
- On GitHub since 2024-05-15, last push 2026-10-29, 29 commits on dev.
- The pin is 2 commits behind dev; the corpus answers from the pinned code, not the newest.
Licence on GitHub and in the corpus
GitHub reported MIT for EzeibekweEmma/object-detection-app on 2026-10-31, and the LICENSE file at commit b519d0a5f6 was reviewed as MIT. They match, so answers from this corpus carry the same terms as the live repository.
Contributors
Ezeibekwe Emmanuel (@EzeibekweEmma) has 1 selected repository on the hub.
Using XERJ with object-detection-app
- ripgrep vs a code index for coding agents: 30 tasks
- Best MCP servers for local code search in 2026, compared
- Best grep alternative for AI coding agents (2026)
- Ask questions about a GitHub repo without cloning it
The prompt
Paste it into your AI agent. It clones EzeibekweEmma/object-detection-app at the pinned commit and indexes it on your machine.
Search the GitHub repository EzeibekweEmma/object-detection-app with XERJ (https://hub.xerj.org/corpus/ezeibekweemma--object-detection-app). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/EzeibekweEmma/object-detection-app object-detection-app && git -C object-detection-app checkout b519d0a5f674170df40918dcdcf7c128081d08fa 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./object-detection-app --url http://127.0.0.1:9200 --prefix object-detection-app --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: MIT. Keep the copyright notice and credit the authors.
Related
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Stats: GitHub API, fetched 2026-10-31. Snapshot: the git tree at the pinned commit. Selected work and consent: the XERJ registry.