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How to Configure the Hardware for using the AI

Camera Setup

Resolution: The Camera should produce a good quality image of the print bed area. It is recomended to use a RPi-based camera like the Raspberry Pi Camera Module 3 or the Raspbeerry Pi Camera v2. The camera must run with a minimum resoltuion of 640 x 640 pixels. It is highly recomended to run the camera quality at a higher resolution than this, because the camera may be used for other purposes in addition to AI monitoring.

As a result, it is recomended that the camera be run in a resolution of 1920 x 1080 pixels.

Quality: The camera streamer has a quality setting that ranges from 0-100, with 100 being the best quality. It is recomended to run the camera in a quality of 100 or as close to 100 as possible, with the absolute minimum being a quality of 80.

Framerate: The camera framerate (FPS) does not need to be high in order to run the AI. The AI software analyzes the current image every 10 seconds. A frame rate of 1 frame per second is sufficient to run the AI software, however it is recomended to use a frame rate of 5 frames per second to run the AI software.

An example streamer service file has been created and is located at streamer/printwatch-streamer-v3.service in this repository.


Position the Camera to:

  1. Keep the entire print bed and print area within frame
  2. Maximize the print bed and print area in the frame
    • Ideally print bed and area are edge-to-edge in the camera frame
  3. Remove items in the background/outside the printer in the Camera frame
    • These may cause false-Positive detections

The BambuLabs printers are a good example of camera placement (model P1S pictured):



  • The print bed and print area should be well-lit and visible with the human eye
    • The rule of thumb for Computer-Vision based AI is that if a person is unable to clearly see what is in the frame, then neither will the AI.
  • Do not over-expose the print bed and print object with too much light
  • A good balance between well-lit and not too bright is required (see examples below).

Good Example: Object is visible, and not overexposed to light


Bad Example: Not enough lighting, object is not clearly visible


Bad Example: Too much lighting, object is overexposed



If there are items within the print chamber that are causing issues with the AI software, such as False-Positives, they can be addressed in two ways:

  1. Sample images from the camera inside the printer enclosure and train with it to cancel out the False-Positives
  2. Add blockout regions inside the AI software.
  3. A blockout region replaces the selected camera frame areas with black pixels when being sent to the AI model, essentially removing the item from the frame
  4. This does not change the camera stream or stream preview

Example of #2

The purge shoot on the BambuLabs may get some pieces of spaghetti stuck and visible inside of the frame, and this may cause the AI to unwantingly detect it:


The AI software will draw over the selected area with black pixels so the AI model ignores anything in this region: