TensorFlow.js-powered Interactive Model Visualizers for standard perception tasks embeddable anywhere in the web.
Supported tasks:
- Image Classification
- Object Detection
- Image Segmentation
The Interactive Visualizer supports any model coming with a metadata JSON file
formatted following the supported tasks standards. This metadata file is passed
at runtime to the visualizer as URL query parameter (e.g.
https://visualizerHostedUrl/?modelMetadataUrl=https://myModelMetadataUrl/metadata.json
).
The visualizer will then load its UI and behave according to the task defined by the model metadata.
NOTE: standards definition is WIP. Here's an example of such metadata for an image classifier model: https://storage.googleapis.com/tfhub-visualizers/google/aiy/vision/classifier/plants_V1/1/metadata.json.
This project was generated with Angular CLI version 10.1.3.
Run ng serve
for a dev server. Navigate to http://localhost:4200/
. The app
will automatically reload if you change any of the source files.
Run ng build
to build the project. The build artifacts will be stored in the
dist/
directory. Use the --prod
flag for a production build.
Run ng test
to run the tests.
Karma is providing the
testing environment, and Jasmine is used for unit
testing.
Additionally run ng lint
to check for the linter warnings/errors.