facenet-pytorch

by timesformer

Deep face recognition with triplet loss embeddings

1.1Mdl/month

23Mparams

HuggingFace Use in Pipeline

Identifiers

Model ID

timesformer/facenet-pytorch

Feature URI

mixpeek://face_identity@v1/timesformer_facenet_v1

Overview

FaceNet maps face images to a compact 128-dimensional embedding space where distances directly correspond to face similarity. Trained using triplet loss, it achieves 99.63% accuracy on the Labeled Faces in the Wild benchmark.

On Mixpeek, FaceNet provides face embedding extraction for identity-based search — find all appearances of a person across your video and image library.

Architecture

InceptionResnetV1 backbone fine-tuned with triplet loss on VGGFace2 dataset. Produces 512-dim or 128-dim face embeddings. Pre-processes with MTCNN face detection and alignment.

Mixpeek SDK Integration

import { Mixpeek } from "mixpeek";

const mx = new Mixpeek({ apiKey: "API_KEY" });

await mx.collections.ingest({
  collection_id: "my-collection",
  source: { url: "https://example.com/video.mp4" },
  feature_extractors: [{
    name: "face_detection",
    version: "v1",
    params: {
      model_id: "timesformer/facenet-pytorch"
    }
  }]
});