Models

Explore pre-trained TensorFlow.js models that can be used in any project out of the box.

Image classification

Classify images with labels from the ImageNet database (MobileNet).

Object detection

Localize and identify multiple objects in a single image (Coco SSD).

Body segmentation

Segment person(s) and body parts in real-time (BodyPix).

Pose estimation

Estimate human poses in real-time (PoseNet).

Text toxicity detection

Score the perceived impact a comment may have on a conversation, from "Very toxic" to "Very healthy" (Toxicity).

Universal sentence encoder

Encode text into embeddings for NLP tasks such as sentiment classification and textual similarity (Universal Sentence Encoder).

Speech command recognition

Classify 1-second audio snippets from the speech commands dataset (speech-commands).

KNN Classifier

Utility to create a classifier using the K-Nearest-Neighbors algorithm. Can be used for transfer learning.

Simple face detection

Detect faces in images using a Single Shot Detector architecture with a custom encoder (Blazeface).

Semantic segmentation

Run semantic segmentation in the browser (DeepLab).

Face landmark detection

Predict 486 3D facial landmarks to infer the approximate surface geometry of human faces.

Hand pose detection

Palm detector and hand-skeleton finger tracking model. Predict 21 3D hand keypoints per detected hand.

Natural language question answering

Answer questions based on the content of a given passage of text using BERT.