The app loads a TensorFlow.js CLIP model from modelzoo.js and h5 weights from HF. CLIP encodes images and texts into a 512-dimensional embedding space. The app captures the webcam stream and encodes it into a 512-dimensional vector. Then it compares the vector with the embeddings of provided classes and if the target class is found, sound is played and the class is displayed.
-
Notifications
You must be signed in to change notification settings - Fork 0
Zero-shot object detection in the browser with CLIP and TensorFlow.js
jseeio/detect
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Zero-shot object detection in the browser with CLIP and TensorFlow.js
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published