Video Management API - slow video processing inside container on MacBook
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- Dominant language
- Python
- Stars
- 2.5k
- Forks
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- Avg merge
- 1d 14h
- Merged PRs (30d)
- 133
Description
Search before asking
- I have searched the Inference issues and found no similar bug report.
Bug
The same workflow tested, reporting only latency for single frame processing inside WorkflowRunner.run_workflow(...) function:
MacBook, bare metal in script using InferencePipeline directly - ~40ms
MacBook, inside docker container, behind API - ~110ms
MacBook dies - 100% CPU utilisation when InferencePipeline is running inside container 😢
Environment
No response
Minimal Reproducible Example
No response
Additional
No response
Are you willing to submit a PR?
- Yes I'd like to help by submitting a PR!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with inference/core/interfaces/stream/model_handlers/workflows.py and the referenced WorkflowRunner.run_workflow(...) path. Compare the reported bare-metal InferencePipeline latency with the containerized API path and investigate the 100% CPU behavior on a MacBook; done means the container no longer shows the reported processing slowdown or CPU exhaustion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker, python
- Domain
- api, computer-vision, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100