yolos-tiny

by hustvl

You Only Look at One Sequence — ViT-based real-time object detection

76Kdl/month

278likes

6Mparams

HuggingFace Use in Pipeline

Identifiers

Model ID

hustvl/yolos-tiny

Feature URI

mixpeek://image_extractor@v1/hustvl_yolos_tiny_v1

Overview

YOLOS adapts the Vision Transformer (ViT) architecture for object detection by simply appending detection tokens to the input sequence. It demonstrates that a pure transformer can perform object detection without any convolutional components.

On Mixpeek, YOLOS Tiny provides a lightweight, fast alternative to DETR for object detection tasks where speed is prioritized over maximum accuracy.

Architecture

Vision Transformer (ViT-Tiny) with 12 layers. Appends 100 learnable detection tokens to the image patch sequence. Uses bipartite matching loss like DETR.

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: "object_detection",
    version: "v1",
    params: {
      model_id: "hustvl/yolos-tiny"
    }
  }]
});