Seeed-Jetson-DevelopTool / deploy-efficient-vision-engine
CLAUDE.md57 starsChanged 4 months agoMITView on GitHub
Use for Seeed Jetson topic "Efficient Multi-Task Vision Inference Engine Deployment on Jetson". Includes local references and execution-safe workflow with prerequisites, commands, and validation checks.
In this repository297 other files it gives its agents.
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- The first 60 shown.
The file
We split this CLAUDE.md into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 10
Read references/source.body.md first to extract prerequisites and command order.
- Distinctive: line 37
Do not skip prerequisite checks.
- Distinctive: line 38
If command output differs from expected behavior, pause and ask user before destructive steps.
- Distinctive: line 39
Prefer reversible changes and include verification commands.
≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Efficient Multi-Task Vision Inference Engine Deployment on Jetson
Execution model
- Confirm board model and JetPack/L4T version before applying commands.
- Read
references/source.body.mdfirst to extract prerequisites and command order. - Execute steps in smallest reproducible sequence and record command outputs.
- Validate final expected results and keep rollback notes.
Source
- Original markdown:
/home/darklee/tmp/jetson-develop/refer-参考完后会清除/Application/Computer_Vision/Efficient_Multi-Task_Vision_Inference_Engine_Deployment_on_Jetson.md - Scope:
application(Computer_Vision)
Topic summary
Visual Perception Engine is a cutting-edge framework that revolutionizes robotic perception by eliminating redundant computations through shared backbone networks. Unlike traditional approaches where each
Key sections
- Introduction
- Prerequisites
- Technical Highlights
- Environment Setup
- Performance Testing
- Real-time camera input for inference
- Other Applications
- Resources
- Tech Support & Product Discussion
Reference files
references/source.mdreferences/source.body.md
Agent instruction
- Do not skip prerequisite checks.
- If command output differs from expected behavior, pause and ask user before destructive steps.
- Prefer reversible changes and include verification commands.
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