Add AIConfigPanel: redesigned AI configuration UI (model cards + prec…#75
Open
eshankiyer wants to merge 4 commits into
Open
Add AIConfigPanel: redesigned AI configuration UI (model cards + prec…#75eshankiyer wants to merge 4 commits into
eshankiyer wants to merge 4 commits into
Conversation
…ision with each inference request
…gmentation dispatcher
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This PR adds AIConfigPanel.tsx, a redesigned AI configuration interface for the PanTS demo. Segmentation models are presented as selectable cards (SuPreM, ePAI, Atlas-Net, MedFormer, R-Super, OpenVAE), and a precision selector (FP32 / FP16 / INT8) has been added.
The component preserves the existing upload and inference flow from InferenceUpload.tsx: chunked upload, finalize-upload, run-epai-inference, and status polling are unchanged. The only functional addition is that the selected precision is included with the inference request.
No existing files are modified; this introduces a single new component.