CLIP Image-Text Matching
Orchestra-Research/AI-Research-SKILLs
Explains OpenAI's CLIP model for zero-shot image classification, image-text similarity, semantic image search and content moderation, with install steps and code patterns.
Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3.
Install Video Camera Demos
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demos --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .claude/skills/video-camera-demos && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .claude/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demosType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demos --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .agents/skills/video-camera-demos && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .agents/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demos --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .cursor/skills/video-camera-demos && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .cursor/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demos --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .gemini/skills/video-camera-demos && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .gemini/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demosInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .github/skills/video-camera-demos && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .github/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill video-camera-demos --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos .opencode/skills/video-camera-demos && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "video-camera-demos" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos into .opencode/skills/video-camera-demos/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-camera-demos", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
video-camera-demos- GitHub stars
- 331
- Token cost
- ~626 tokens
- SKILL.md length
- 281 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 157
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3.
- Pytorch-yolo-v3
- SKILL.md covers Route first, Safe operating policy and What to consult inside this…
- Runs Python scripts from its folder; calls python
- Tasks that involve Deep learning
What it does
Video Camera Demos is an agent skill from VectorSpaceLab/AREX-Skill. Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3.
Its SKILL.md is about 630 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/troubleshooting.md`, `references/video-camera-workflows.md` and `scripts/check_video_demo_args.py`).
It sits in AI & LLM Engineering, covering Deep learning and Computer vision. It works with PyTorch. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.
When your agent uses it
- Pytorch-yolo-v3
- Tasks that involve Deep learning
- Tasks that involve Computer vision
Example prompts
- “/video-camera-demos”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Video Camera Demos loads about 626 tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 27 tokens; SKILL.md has 281 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 281 words, ~626 tokens.
Download SKILL.mdSave it as
.claude/skills/video-camera-demos/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- video-camera-demos
- description
- Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- NO_LICENSE
Video and Camera Demos
Use this sub-skill when a user asks about the repository's video-file demo, webcam demo, or optional half-precision video demo. Keep the interaction focused on safe preflight, command construction, and troubleshooting for these demo entrypoints.
Route first
- Image or batch-image detection: route to
../image-detection/SKILL.md. - Configuration files, model architecture, class names, weight formats, or weight-loading internals: route to
../model-and-config/SKILL.md. - Training, dataset preparation for training, and model fine-tuning are out of scope for this sub-skill.
Safe operating policy
Do not start a GUI loop, webcam capture, video capture, model inference, download, or weight fetch as a default check.
Before any full demo run, confirm the user has an intended display path, an accessible video file or camera, required local config/weight files, OpenCV, PyTorch, and permission to use the device.
Treat CUDA and half precision as optional. Do not claim a full fp16 run is verified unless it was actually run on a CUDA/fp16-capable GPU with the user's files and display.
Prefer the bundled safe helper for parser/source checks:
bash python scripts/check_video_demo_args.py --repo-root <repo-root>Run it from this sub-skill directory or adjust the script path to wherever this skill tree is installed. The helper only invokes
-hand source inspection; it must not open a webcam, video, display, or model.Use the bundled dry-run/launcher wrapper to prepare full demo commands without opening capture/display by default:
bash python scripts/run_video_demo.py --repo-root <repo-root> --mode video --video <video-file> --weights <weights-file>Add
--execute --allow-displayonly after the user explicitly approves an interactive OpenCV run; camera mode also requires--allow-camera.
What to consult inside this skill
references/video-camera-workflows.mdfor supported flags, run gates, and demo-specific workflow notes.references/troubleshooting.mdfor known failure modes and source-reviewed pitfalls.scripts/check_video_demo_args.pyfor deterministic, safe verification that the expected demo scripts and argparse help are present in a user's checkout.
© VectorSpaceLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references) in skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/troubleshooting.md
- references/video-camera-workflows.md
- scripts/check_video_demo_args.py
- scripts/run_video_demo.py
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Video Camera Demos next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Video Camera Demos this skillVectorSpaceLab/AREX-Skill | 331 | — | ~626 | Automated safety check: Pass | Apache-2.0 | |
| CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Scholar Computejoshzyj/open-scholar-skill | 168 | — | ~15k | Automated safety check: Pass | Custom licence | |
| Computer Vision Pipelinecuriositech/some_claude_skills | 244 | — | ~4k | Automated safety check: Pass | MIT | |
| Tao Train Image ClassificationNVIDIA/skills | 3.6k | — | ~3.6k | Automated safety check: Notes | Apache-2.0 | |
| Matlab Integrate Pytorch Visionmatlab/matlab-agentic-toolkit | 1.1k | — | ~3.7k | Automated safety check: Pass | Custom licence |
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Related
Works with
Categories
Questions about Video Camera Demos
What does Video Camera Demos do?
Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3. Video Camera Demos is an agent skill from VectorSpaceLab/AREX-Skill. Guide safe video-file, webcam, and optional half-precision demo use for pytorch-yolo-v3.
When should I use Video Camera Demos?
Video Camera Demos fits situations like: pytorch-yolo-v3; tasks that involve Deep learning; tasks that involve Computer vision.
How do I install Video Camera Demos in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos in VectorSpaceLab/AREX-Skill) into .claude/skills/video-camera-demos in your project. Claude Code loads it when a task matches its description.
How do I install Video Camera Demos in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a codex`. Or copy the skill folder (skills/repositories/repo-skills/pytorch-yolo-v3/sub-skills/video-camera-demos in VectorSpaceLab/AREX-Skill) into .agents/skills/video-camera-demos in your project. Codex loads it when a task matches its description.
Can I use Video Camera Demos in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill video-camera-demos -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/video-camera-demos, .gemini/skills/video-camera-demos, .github/skills/video-camera-demos and .opencode/skills/video-camera-demos in your project.
What does Video Camera Demos need to run?
Going by SKILL.md and its folder, Video Camera Demos needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Video Camera Demos access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Video Camera Demos safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Video Camera Demos use?
Video Camera Demos is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Video Camera Demos use?
About 626 tokens (SKILL.md is roughly 2.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.4k tokens, read only when the agent opens those files.
What are the alternatives to Video Camera Demos?
Skills that share tags, products or a category with Video Camera Demos: CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Scholar Compute (joshzyj/open-scholar-skill, 168 stars), Computer Vision Pipeline (curiositech/some_claude_skills, 244 stars) and Tao Train Image Classification (NVIDIA/skills, 3.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Video Camera Demos?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 331 GitHub stars. The repository holds 157 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.