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README.md
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@@ -8,27 +8,27 @@ https://huggingface.co/facebook/sam-vit-base with ONNX weights to be compatible
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## Usage (Transformers.js)
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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/@
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```bash
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npm i @
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```
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**Example:** Perform mask generation with `Xenova/sam-vit-base`.
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```js
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import { SamModel, AutoProcessor, RawImage } from
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// Load model and processor
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const model = await SamModel.from_pretrained(
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const processor = await AutoProcessor.from_pretrained(
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// Prepare image and input points
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const img_url =
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const raw_image = await RawImage.read(img_url);
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const input_points = [[[340, 250]]];
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// Process inputs and perform mask generation
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const inputs = await processor(raw_image, input_points);
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const outputs = await model(inputs);
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// Post-process masks
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@@ -48,9 +48,9 @@ console.log(scores);
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// dims: [ 1, 1, 3 ],
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// type: 'float32',
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// data: Float32Array(3) [
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// 0.
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//
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// 0.
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// ],
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// size: 3
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// }
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## Usage (Transformers.js)
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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/@huggingface/transformers) using:
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```bash
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npm i @huggingface/transformers
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```
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**Example:** Perform mask generation with `Xenova/sam-vit-base`.
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```js
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import { SamModel, AutoProcessor, RawImage } from "@huggingface/transformers";
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// Load model and processor
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const model = await SamModel.from_pretrained("Xenova/sam-vit-base");
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const processor = await AutoProcessor.from_pretrained("Xenova/sam-vit-base");
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// Prepare image and input points
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const img_url = "https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/corgi.jpg";
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const raw_image = await RawImage.read(img_url);
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const input_points = [[[340, 250]]];
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// Process inputs and perform mask generation
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const inputs = await processor(raw_image, { input_points });
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const outputs = await model(inputs);
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// Post-process masks
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// dims: [ 1, 1, 3 ],
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// type: 'float32',
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// data: Float32Array(3) [
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// 0.9742214679718018,
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// 1.002995491027832,
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// 0.9613651037216187
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// ],
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// size: 3
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// }
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