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Thermal video processing

June 13, 2019 Developer 1 minute, 17 seconds

In the field

  • A thermal camera in the fields spots something a moving warm 'animal'.
  • The thermal camera records the 'animal' until it 'stops seeing movement'. The raw data from our lepton3 camera for this time is then saved into our custom *.CPTV format.
  • The date-stamped file is then uploaded through the internet or by using side kick to our API server.

On the API server

  • Once a CPTV file makes it into our cloud one of our thermal video processors will pick up the file and process it. (
  • First the processor will extract the metadata from the CPTV.
  • Then it will run the video through our machine learning model. This works in three stages:
    1. Possible animals called tracks are extracted from the video
    2. The tracks are feed into our machine learning model
    3. A MP4 videos is produced so we humans can view it.
  • The processor takes the results and decides what tags to identify the track/video with.
  • The processor uploads the track definitions and MP4 to the api server.

Setting up a test server on your machine

To try this yourself you first need to download the four projects involved:

Then:

  1. Run the cacophony-api using the ./run command
  2. Set up the paths to the classifier-pipeline and virtural env in your cacophony-processing yaml
  3. Run cacophony-processing: python thermal-processing.py
  4. Upload a CPTV file to the api server. (Any easy way to to this is to run test\pytest test_thermal_device.py in the cacophony-api project)
  5. Wait for the cacophony-processing process to poll for the file and process it.