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https://github.com/tensorflow/tfjs-models
Pretrained models for TensorFlow.js
https://github.com/tensorflow/tfjs-models
Last synced: 6 days ago
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Pretrained models for TensorFlow.js
- Host: GitHub
- URL: https://github.com/tensorflow/tfjs-models
- Owner: tensorflow
- License: apache-2.0
- Created: 2018-04-03T21:04:35.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-10-15T22:00:27.000Z (19 days ago)
- Last Synced: 2024-10-18T10:07:55.534Z (16 days ago)
- Language: TypeScript
- Homepage: https://js.tensorflow.org
- Size: 165 MB
- Stars: 14,046
- Watchers: 276
- Forks: 4,339
- Open Issues: 193
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
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README
# Pre-trained TensorFlow.js models
This repository hosts a set of pre-trained models that have been ported to
TensorFlow.js.The models are hosted on NPM and unpkg so they can be used in any project out of the box. They can be used directly or used in a transfer learning
setting with TensorFlow.js.To find out about APIs for models, look at the README in each of the respective
directories. In general, we try to hide tensors so the API can be used by
non-machine learning experts.For those interested in contributing a model, please file a [GitHub issue on tfjs](https://github.com/tensorflow/tfjs/issues) to gauge
interest. We are trying to add models that complement the existing set of models
and can be used as building blocks in other apps.## Models
Type
Model
Demo
Details
Install
Images
MobileNet
live
Classify images with labels from the ImageNet database.
npm i @tensorflow-models/mobilenet
source
Hand
live
Real-time hand pose detection in the browser using TensorFlow.js.
npm i @tensorflow-models/hand-pose-detection
source
Pose
live
An API for real-time human pose detection in the browser.
npm i @tensorflow-models/pose-detection
source
Coco SSD
Object detection model that aims to localize and identify multiple objects in a single image. Based on the TensorFlow object detection API.
npm i @tensorflow-models/coco-ssd
source
DeepLab v3
Semantic segmentation
npm i @tensorflow-models/deeplab
source
Face Landmark Detection
live
Real-time 3D facial landmarks detection to infer the approximate surface geometry of a human face
npm i @tensorflow-models/face-landmarks-detection
source
Audio
Speech Commands
live
Classify 1 second audio snippets from the speech commands dataset.
npm i @tensorflow-models/speech-commands
source
Text
Universal Sentence Encoder
Encode text into a 512-dimensional embedding to be used as inputs to natural language processing tasks such as sentiment classification and textual similarity.
npm i @tensorflow-models/universal-sentence-encoder
source
Text Toxicity
live
Score the perceived impact a comment might have on a conversation, from "Very toxic" to "Very healthy".
npm i @tensorflow-models/toxicity
source
Depth Estimation
Portrait Depth
live
Estimate per-pixel depth (the distance to the camera center) for a single portrait image, which can be further used for creative applications such as 3D photo and relighting.
npm i @tensorflow-models/depth-estimation
source
General Utilities
KNN Classifier
This package provides a utility for creating a classifier using the K-Nearest Neighbors algorithm. Can be used for transfer learning.
npm i @tensorflow-models/knn-classifier
source
## Development
You can run the unit tests for any of the models by running the following
inside a directory:`yarn test`
New models should have a test NPM script (see [this](./mobilenet/package.json) `package.json` and `run_tests.ts` [helper](./mobilenet/run_tests.ts) for reference).
To run all of the tests, you can run the following command from the root of this
repo:`yarn presubmit`