Update README.md

README.md

@@ -5,4 +5,49 @@ pipeline_tag: depth-estimation
 
 https://huggingface.co/LiheYoung/depth-anything-base-hf with ONNX weights to be compatible with Transformers.js.
 
+## Usage (Transformers.js)
+
+If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@xenova/transformers) using:
+```bash
+npm i @xenova/transformers
+```
+
+**Example:** Depth estimation with `Xenova/depth-anything-base-hf`.
+
+```js
+import { pipeline } from '@xenova/transformers';
+
+// Create depth-estimation pipeline
+const depth_estimator = await pipeline('depth-estimation', 'Xenova/depth-anything-base-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:
+
+```js
+output.depth.save('depth.png');
+```
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/5olbEauiVjwNqLd55EyI1.png)
+
+---
+
 Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).