bhaney / vision-service-examples

Example code for using the viam vision service

Viam Vision Service

This repo gives an example of creating a video stream, using the Viam vision service, and also importing openCV.

The example uses the user's webcam as a robot, adds an object detection model using Viam's vision service, and then draws a box around the object.

It uses an EfficientDet tflite model from the tensorflow model zoo.

Go

program located in the go directory. run using go run cmd.go

Python

program located in the python directory. Needs the Viam Python SDK, can download it with pip install git+https://github.com/viamrobotics/python-sdk.git run using python cmd.py

app.viam.com

You can also configure a stream of detections completely through the app. You can see an example config in viam_app_config.json. Once you have a robot with a webcam connected to app.viam.com:

In CONFIG -> Services, configure your object detection model

{
  "register_models": [
    {
      "parameters": {
        "model_path": "/full/path/to/vision-service-examples/data/effdet0.tflite",
        "num_threads": 1
      },
      "name": "find_objects",
      "type": "tflite_detector"
    }
  ]
}

Then, in CONFIG -> Components, configure both a "webcam" model camera, and a "transform" model camera. Give the "transform" model the following attributes:

{
  "stream": "color",
  "source": "the_webcam_name",
  "pipeline": [
      {
          "attributes": {
              "confidence_threshold": 0.5,
              "detector_name": "find_objects"
          },
          "type": "detections"
      }
  ]
}

Save your config, wait for the robot to reload, and then go to the CONTROL tab to see the stream of detections.

Note

• The tflite files need to be on the robot, and the path needs to be the path to their location on the robot.
• Make sure to use full paths to the model and label file when registering the detector.
• If connecting through GRPC, use your robot's address and secret from app.viam.com
• Make sure that the camera name matches in the script and the name of the camera you are using.