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).

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Object detection

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

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Body segmentation

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

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Pose estimation

Estimate human poses in real-time (PoseNet).

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Text toxicity detection

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

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Universal sentence encoder

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

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Speech command recognition

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

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KNN Classifier

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

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Simple face detection

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

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Semantic segmentation

Run semantic segmentation in the browser (DeepLab).

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Face landmark detection

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

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Hand pose detection

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

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Natural language question answering

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

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