PrintWatch Release Notes

The official Release Notes for PrintWatch 1.1.1.

1.0 PrintWatch 1.1.1 Release Notes

The document formatted release notes for PrintWatch can be found here.

1.1 Major Features

The major features and their descriptions are listed below:

• Tracking Algorithm: the algorithm used to track defects has changed significantly. This will help eliminate noisy backgrounds causing triggers.
• PrintWatch Tab: the PrintWatch tab in OctoPrint has been reworked. A live plot has been added below the PrintWatch preview. The live plot indicates the ‘defectiveness’ level of the print.
• PrintWatch Settings: the PrintWatch settings tab in OctoPrint has been reworked. The settings are organized in tabs. The following settings have been added:
  • The following settings have been added:
    • Stop on trigger
    • Action Threshold
    • Notification Threshold
  • The following settings have been removed:
    • Buffer percentage
• Email Notification: the Email notification has been reworked. The user may now specify to receive warning emails and emails notifying of actions taken. The email uses a newer and sleeker template. 
  • The following has been added:
    • Text notification of the action
    • Button link routing to the Web Application allowing users to manage the printer
  • The following has been removed:
    • Image preview
• Endpoint routing: re-routing of endpoints used for various actions.
• Video streaming module: the video frame acquisition method has changed from a continuous stream to a single snapshot at the time of inference.
  • The following has been removed:
    • VideoStreamer frame queue
  • The following has been added:
    • VideoStreamer snapshot
• Version monitoring: the PrintWatch OctoPrint plugin version is now sent to the server to enable backward compatibility for future releases.

1.2 Bug Fixes

There are no previously known bugs

1.3 Known Issues

There are no known issues.

1.4 Future Features

The major features planned for the next release are listed below:

• Report image button: button added to report an image as containing an issue. This helps train the Machine Learning models.
• Bed clearing: a Machine Learning model/CV algorithm to indicate that the bed is clear and ready for another print. This is useful for automated printing or batched jobs.
• Robust Print defect support: the Machine Learning models will support detection of more various types of print defects in addition to common QC related checks.
• Robust notifications: receive notifications via telegram, discord, and more. Contact us to request a platform.
• Status alerts: receive status notifications set by your criteria. E.g. receive a notification when the print job is finished.
• ROI Slicing: select the area within the frame to run detections on. This is good for users that have noisy backgrounds, high resolution cameras, and low amounts of hardware (this allows for one camera to be used to detect on multiple printers). This is currently supported when using the API.
• Web App Expansion: the Web Application capabilities will be expanded in addition to a rework on the UI.