Add support for Depth Anything (https://github.com/xenova/transformers.js/pull/534). See here for the list of available models.
Example: Depth estimation with Xenova/depth-anything-small-hf.
import { pipeline } from '@xenova/transformers';
// Create depth-estimation pipeline
const depth_estimator = await pipeline('depth-estimation', 'Xenova/depth-anything-small-hf');
// Predict depth map for the given image
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/bread_small.png';
const output = await depth_estimator(url);
// {
// predicted_depth: Tensor {
// dims: [350, 518],
// type: 'float32',
// data: Float32Array(181300) [...],
// size: 181300
// },
// depth: RawImage {
// data: Uint8Array(271360) [...],
// width: 640,
// height: 424,
// channels: 1
// }
// }
You can visualize the output with:
output.depth.save('depth.png');
| Input image | Visualized output |
|---|---|
Online demo: https://huggingface.co/spaces/Xenova/depth-anything-web
Example video:
https://github.com/xenova/transformers.js/assets/26504141/bbac3db6-8d8f-4386-a212-7e66ca616a0d
Fix typo in tokenizers.js (https://github.com/xenova/transformers.js/pull/518)
Return empty tokens array if text is empty after normalization (https://github.com/xenova/transformers.js/pull/535)
Full Changelog: https://github.com/xenova/transformers.js/compare/2.14.0...2.14.1
Fetched April 7, 2026