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I have been experimenting with ControlNet and was wondering if it's possible to introduce a feature to randomly pull from a directory of pre-processed images (e.g., OpenPose skeletons) instead of manual selection. This would allow users to define a set directory and use 'Generate Forever' to test how a model interacts with various poses without manual intervention.
I attempted to automate this via an external shell script that overwrites a static file (current_pose.png) at set intervals, hoping it would force SwarmUI to pull the current image with the same filename it had already loaded. This fails because the image is cached by the UI/backend (I think).
Since the filename doesn't change, the system reuses the previous image data rather than polling the disk for the updated file.
Proposed Solution: It would be ideal to have a 'Randomize from Folder' toggle in the ControlNet options.
This feature would significantly improve the workflow for creators doing bulk testing, dataset generation, or 'discovery' runs where the goal is to see a variety of compositions quickly, vs trying to use wildcards to force inexact poses.
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I have been experimenting with ControlNet and was wondering if it's possible to introduce a feature to randomly pull from a directory of pre-processed images (e.g., OpenPose skeletons) instead of manual selection. This would allow users to define a set directory and use 'Generate Forever' to test how a model interacts with various poses without manual intervention.
I attempted to automate this via an external shell script that overwrites a static file (current_pose.png) at set intervals, hoping it would force SwarmUI to pull the current image with the same filename it had already loaded. This fails because the image is cached by the UI/backend (I think).
Since the filename doesn't change, the system reuses the previous image data rather than polling the disk for the updated file.
Proposed Solution: It would be ideal to have a 'Randomize from Folder' toggle in the ControlNet options.
This feature would significantly improve the workflow for creators doing bulk testing, dataset generation, or 'discovery' runs where the goal is to see a variety of compositions quickly, vs trying to use wildcards to force inexact poses.
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