1

index.js

@@ -1,4 +1,6 @@
-import { AutoProcessor, VitMatteForImageMatting, RawImage,  Tensor, cat  } from '@xenova/transformers';
+import { AutoProcessor, VitMatteForImageMatting, RawImage,  Tensor, cat  } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.10.1';
+
+env.allowLocalModels = false;
 
 // Load processor and model
 const processor = await AutoProcessor.from_pretrained('Xenova/vitmatte-small-composition-1k');
@@ -13,15 +15,12 @@ const inputs = await processor(image, trimap);
 
 // Predict alpha matte
 const { alphas } = await model(inputs);
-console.log('alpha', alphas)
 // Tensor {
 //   dims: [ 1, 1, 640, 960 ],
 //   type: 'float32',
 //   size: 614400,
 //   data: Float32Array(614400) [ 0.9894027709960938, 0.9970508813858032, ... ]
 // }
-//
-// import { Tensor, cat } from '@xenova/transformers';
 
 // Visualize predicted alpha matte
 const imageTensor = new Tensor(
@@ -44,3 +43,4 @@ const imageData = cat([imageTensor, alphaChannel], 0);
 // Save output image
 const outputImage = RawImage.fromTensor(imageData);
 outputImage.save('output.png');
+