voyager-run

Run Inference

Execute inference on Axelera AI hardware with various input sources

Use This Skill When / Not When

• Use when: a model/pipeline is already selected and the user wants to execute inference.py with a video, image, USB, RTSP, or dataset source.
• Not when: they want a packaged end-to-end solution with validation artifacts -- route to voyager-launch.
• Not when: a custom model must be compiled or quantized first -- route to voyager-deploy.

Instructions

Run inference with the specified configuration: $ARGUMENTS

{{INCLUDE common/voyager-sdk-setup.md}}

{{INCLUDE common/voyager-task-integration.md}}

{{INCLUDE common/examples-catalog.md}}

Step 1: Environment Verification

• Ensure environment is activated:

  source venv/bin/activate
  

• Read .voyager-runtime.json. Only verify hardware directly when execution.mode is execute_on_device:

  axdevice
  

  In package_for_linux mode, return Voyager SDK commands and the package-only caveat instead of claiming hardware execution.

Step 2: Parse Arguments

• Model/pipeline name (required)
• Input source (camera, video, image, dataset, RTSP)
• Display options
• Output options
• Examples-first: if the user described a task rather than naming a model, check common/examples-catalog.md for a ready-made example (or route to voyager-launch).

Step 3: Input Source Configuration

USB Camera:

./inference.py <model> usb:0           # First USB camera
./inference.py <model> usb:1           # Second USB camera
./inference.py <model> usb:0 usb:1     # Multiple cameras
./inference.py <model> usb:0:640x480@30

Video File:

./inference.py <model> /path/to/video.mp4
./inference.py <model> media/traffic1_1080p.mp4

Image File:

./inference.py <model> /path/to/image.jpg
./inference.py <model> /path/to/images/*.jpg   # Multiple images

RTSP Stream:

./inference.py <model> rtsp://user:pass@ip:port/stream