Update index.js

index.js

@@ -1,325 +1,325 @@
-import { SamModel, AutoProcessor, RawImage, Tensor } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.4';
-
-// Reference the elements we will use
-const statusLabel = document.getElementById('status');
-const fileUpload = document.getElementById('upload');
-const imageContainer = document.getElementById('container');
-const example = document.getElementById('example');
-const maskCanvas = document.getElementById('mask-output');
-const uploadButton = document.getElementById('upload-button');
-const resetButton = document.getElementById('reset-image');
-const clearButton = document.getElementById('clear-points');
-const cutButton = document.getElementById('cut-mask');
-
-// State variables
-let lastPoints = null;
-let isDecoding = false;
-let isMultiMaskMode = false;
-let imageDataURI = null;
-let imageInputs = null;
-let imageEmbeddings = null;
-
-// Constants
-const BASE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/';
-const EXAMPLE_URL = BASE_URL + 'corgi.jpg';
-
-// Preload star and cross images to avoid lag on first click
-const star = new Image();
-star.src = BASE_URL + 'star-icon.png';
-star.className = 'icon';
-
-const cross = new Image();
-cross.src = BASE_URL + 'cross-icon.png';
-cross.className = 'icon';
-
-async function decode() {
-    if (!imageInputs || !imageEmbeddings) {
-        return;
-    }
-    isDecoding = true;
-
-    // Prepare inputs for decoding
-    const reshaped = imageInputs.reshaped_input_sizes[0];
-    const points = lastPoints.map(x => [x.point[0] * reshaped[1], x.point[1] * reshaped[0]])
-    const labels = lastPoints.map(x => BigInt(x.label));
-
-    const input_points = new Tensor(
-        'float32',
-        points.flat(Infinity),
-        [1, 1, points.length, 2],
-    )
-    const input_labels = new Tensor(
-        'int64',
-        labels.flat(Infinity),
-        [1, 1, labels.length],
-    )
-
-    // Generate the mask
-    const { pred_masks, iou_scores } = await model({
-        ...imageEmbeddings,
-        input_points,
-        input_labels,
-    })
-
-    // Post-process the mask
-    const masks = await processor.post_process_masks(
-        pred_masks,
-        imageInputs.original_sizes,
-        imageInputs.reshaped_input_sizes,
-    );
-
-    const data = {
-        mask: RawImage.fromTensor(masks[0][0]),
-        scores: iou_scores.data,
-    };
-    isDecoding = false;
-
-    if (!isMultiMaskMode && lastPoints) {
-        // Perform decoding with the last point
-        decode();
-        lastPoints = null;
-    }
-
-    const { mask, scores } = data;
-
-    // Update canvas dimensions (if different)
-    if (maskCanvas.width !== mask.width || maskCanvas.height !== mask.height) {
-        maskCanvas.width = mask.width;
-        maskCanvas.height = mask.height;
-    }
-
-    // Create context and allocate buffer for pixel data
-    const context = maskCanvas.getContext('2d');
-    const imageData = context.createImageData(maskCanvas.width, maskCanvas.height);
-
-    // Select best mask
-    const numMasks = scores.length; // 3
-    let bestIndex = 0;
-    for (let i = 1; i < numMasks; ++i) {
-        if (scores[i] > scores[bestIndex]) {
-            bestIndex = i;
-        }
-    }
-    statusLabel.textContent = `Segment score: ${scores[bestIndex].toFixed(2)}`;
-
-    // Fill mask with colour
-    const pixelData = imageData.data;
-    for (let i = 0; i < pixelData.length; ++i) {
-        if (mask.data[numMasks * i + bestIndex] === 1) {
-            const offset = 4 * i;
-            pixelData[offset] = 0;       // red
-            pixelData[offset + 1] = 114; // green
-            pixelData[offset + 2] = 189; // blue
-            pixelData[offset + 3] = 255; // alpha
-        }
-    }
-
-    // Draw image data to context
-    context.putImageData(imageData, 0, 0);
-}
-
-function clearPointsAndMask() {
-    // Reset state
-    isMultiMaskMode = false;
-    lastPoints = null;
-
-    // Remove points from previous mask (if any)
-    document.querySelectorAll('.icon').forEach(e => e.remove());
-
-    // Disable cut button
-    cutButton.disabled = true;
-
-    // Reset mask canvas
-    maskCanvas.getContext('2d').clearRect(0, 0, maskCanvas.width, maskCanvas.height);
-}
-clearButton.addEventListener('click', clearPointsAndMask);
-
-resetButton.addEventListener('click', () => {
-    // Update state
-    imageEmbeddings = null;
-    imageDataURI = null;
-
-    // Reset the state
-    imageInputs = null;
-    imageEmbeddings = null;
-    isDecoding = false;
-
-    // Clear points and mask (if present)
-    clearPointsAndMask();
-
-    // Update UI
-    cutButton.disabled = true;
-    imageContainer.style.backgroundImage = 'none';
-    uploadButton.style.display = 'flex';
-    statusLabel.textContent = 'Ready';
-});
-
-async function segment(data) {
-    statusLabel.textContent = 'Extracting image embedding...';
-
-    // Update state
-    imageEmbeddings = null;
-    imageDataURI = data;
-
-    // Update UI
-    imageContainer.style.backgroundImage = `url(${data})`;
-    uploadButton.style.display = 'none';
-    cutButton.disabled = true;
-
-    // Read the image and recompute image embeddings
-    const image = await RawImage.read(data);
-    imageInputs = await processor(image);
-    imageEmbeddings = await model.get_image_embeddings(imageInputs)
-
-    statusLabel.textContent = 'Embedding extracted!';
-}
-
-// Handle file selection
-fileUpload.addEventListener('change', function (e) {
-    const file = e.target.files[0];
-    if (!file) {
-        return;
-    }
-
-    const reader = new FileReader();
-
-    // Set up a callback when the file is loaded
-    reader.onload = e2 => segment(e2.target.result);
-
-    reader.readAsDataURL(file);
-});
-
-example.addEventListener('click', (e) => {
-    e.preventDefault();
-    segment(EXAMPLE_URL);
-});
-
-function addIcon({ point, label }) {
-    const icon = (label === 1 ? star : cross).cloneNode();
-    icon.style.left = `${point[0] * 100}%`;
-    icon.style.top = `${point[1] * 100}%`;
-    imageContainer.appendChild(icon);
-}
-
-// Attach hover event to image container
-imageContainer.addEventListener('mousedown', e => {
-    if (e.button !== 0 && e.button !== 2) {
-        return; // Ignore other buttons
-    }
-    if (!imageEmbeddings) {
-        return; // Ignore if not encoded yet
-    }
-    if (!isMultiMaskMode) {
-        lastPoints = [];
-        isMultiMaskMode = true;
-        cutButton.disabled = false;
-    }
-
-    const point = getPoint(e);
-    lastPoints.push(point);
-
-    // add icon
-    addIcon(point);
-
-    decode();
-});
-
-
-// Clamp a value inside a range [min, max]
-function clamp(x, min = 0, max = 1) {
-    return Math.max(Math.min(x, max), min)
-}
-
-function getPoint(e) {
-    // Get bounding box
-    const bb = imageContainer.getBoundingClientRect();
-
-    // Get the mouse coordinates relative to the container
-    const mouseX = clamp((e.clientX - bb.left) / bb.width);
-    const mouseY = clamp((e.clientY - bb.top) / bb.height);
-
-    return {
-        point: [mouseX, mouseY],
-        label: e.button === 2 // right click
-            ? 0  // negative prompt
-            : 1, // positive prompt
-    }
-}
-
-// Do not show context menu on right click
-imageContainer.addEventListener('contextmenu', e => {
-    e.preventDefault();
-});
-
-// Attach hover event to image container
-imageContainer.addEventListener('mousemove', e => {
-    if (!imageEmbeddings || isMultiMaskMode) {
-        // Ignore mousemove events if the image is not encoded yet,
-        // or we are in multi-mask mode
-        return;
-    }
-    lastPoints = [getPoint(e)];
-
-    if (!isDecoding) {
-        decode(); // Only decode if we are not already decoding
-    }
-});
-
-// Handle cut button click
-cutButton.addEventListener('click', () => {
-    const [w, h] = [maskCanvas.width, maskCanvas.height];
-
-    // Get the mask pixel data
-    const maskContext = maskCanvas.getContext('2d');
-    const maskPixelData = maskContext.getImageData(0, 0, w, h);
-
-    // Load the image
-    const image = new Image();
-    image.crossOrigin = 'anonymous';
-    image.onload = async () => {
-        // Create a new canvas to hold the image
-        const imageCanvas = new OffscreenCanvas(w, h);
-        const imageContext = imageCanvas.getContext('2d');
-        imageContext.drawImage(image, 0, 0, w, h);
-        const imagePixelData = imageContext.getImageData(0, 0, w, h);
-
-        // Create a new canvas to hold the cut-out
-        const cutCanvas = new OffscreenCanvas(w, h);
-        const cutContext = cutCanvas.getContext('2d');
-        const cutPixelData = cutContext.getImageData(0, 0, w, h);
-
-        // Copy the image pixel data to the cut canvas
-        for (let i = 3; i < maskPixelData.data.length; i += 4) {
-            if (maskPixelData.data[i] > 0) {
-                for (let j = 0; j < 4; ++j) {
-                    const offset = i - j;
-                    cutPixelData.data[offset] = imagePixelData.data[offset];
-                }
-            }
-        }
-        cutContext.putImageData(cutPixelData, 0, 0);
-
-        // Download image 
-        const link = document.createElement('a');
-        link.download = 'image.png';
-        link.href = URL.createObjectURL(await cutCanvas.convertToBlob());
-        link.click();
-        link.remove();
-    }
-    image.src = imageDataURI;
-});
-
-
-const model_id = 'Xenova/slimsam-77-uniform';
-statusLabel.textContent = 'Loading model...';
-const model = await SamModel.from_pretrained(model_id, {
-    dtype: 'fp16',
-    device: 'webgpu',
-});
-const processor = await AutoProcessor.from_pretrained(model_id);
-statusLabel.textContent = 'Ready';
-
-// Enable the user interface
-fileUpload.disabled = false;
-uploadButton.style.opacity = 1;
-example.style.pointerEvents = 'auto';
+import { SamModel, AutoProcessor, RawImage, Tensor } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.4';
+
+// Reference the elements we will use
+const statusLabel = document.getElementById('status');
+const fileUpload = document.getElementById('upload');
+const imageContainer = document.getElementById('container');
+const example = document.getElementById('example');
+const maskCanvas = document.getElementById('mask-output');
+const uploadButton = document.getElementById('upload-button');
+const resetButton = document.getElementById('reset-image');
+const clearButton = document.getElementById('clear-points');
+const cutButton = document.getElementById('cut-mask');
+
+// Constants
+const BASE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/';
+const EXAMPLE_URL = BASE_URL + 'corgi.jpg';
+
+// Preload star and cross images to avoid lag on first click
+const star = new Image();
+star.src = BASE_URL + 'star-icon.png';
+star.className = 'icon';
+
+const cross = new Image();
+cross.src = BASE_URL + 'cross-icon.png';
+cross.className = 'icon';
+
+// State variables
+let lastPoints = null;
+let isDecoding = false;
+let isMultiMaskMode = false;
+let imageDataURI = null;
+let imageInputs = null;
+let imageEmbeddings = null;
+
+async function decode() {
+    if (!imageInputs || !imageEmbeddings) {
+        return;
+    }
+    isDecoding = true;
+
+    // Prepare inputs for decoding
+    const reshaped = imageInputs.reshaped_input_sizes[0];
+    const points = lastPoints.map(x => [x.point[0] * reshaped[1], x.point[1] * reshaped[0]])
+    const labels = lastPoints.map(x => BigInt(x.label));
+
+    const input_points = new Tensor(
+        'float32',
+        points.flat(Infinity),
+        [1, 1, points.length, 2],
+    )
+    const input_labels = new Tensor(
+        'int64',
+        labels.flat(Infinity),
+        [1, 1, labels.length],
+    )
+
+    // Generate the mask
+    const { pred_masks, iou_scores } = await model({
+        ...imageEmbeddings,
+        input_points,
+        input_labels,
+    })
+
+    // Post-process the mask
+    const masks = await processor.post_process_masks(
+        pred_masks,
+        imageInputs.original_sizes,
+        imageInputs.reshaped_input_sizes,
+    );
+
+    const data = {
+        mask: RawImage.fromTensor(masks[0][0]),
+        scores: iou_scores.data,
+    };
+    isDecoding = false;
+
+    if (!isMultiMaskMode && lastPoints) {
+        // Perform decoding with the last point
+        decode();
+        lastPoints = null;
+    }
+
+    const { mask, scores } = data;
+
+    // Update canvas dimensions (if different)
+    if (maskCanvas.width !== mask.width || maskCanvas.height !== mask.height) {
+        maskCanvas.width = mask.width;
+        maskCanvas.height = mask.height;
+    }
+
+    // Create context and allocate buffer for pixel data
+    const context = maskCanvas.getContext('2d');
+    const imageData = context.createImageData(maskCanvas.width, maskCanvas.height);
+
+    // Select best mask
+    const numMasks = scores.length; // 3
+    let bestIndex = 0;
+    for (let i = 1; i < numMasks; ++i) {
+        if (scores[i] > scores[bestIndex]) {
+            bestIndex = i;
+        }
+    }
+    statusLabel.textContent = `Segment score: ${scores[bestIndex].toFixed(2)}`;
+
+    // Fill mask with colour
+    const pixelData = imageData.data;
+    for (let i = 0; i < pixelData.length; ++i) {
+        if (mask.data[numMasks * i + bestIndex] === 1) {
+            const offset = 4 * i;
+            pixelData[offset] = 0;       // red
+            pixelData[offset + 1] = 114; // green
+            pixelData[offset + 2] = 189; // blue
+            pixelData[offset + 3] = 255; // alpha
+        }
+    }
+
+    // Draw image data to context
+    context.putImageData(imageData, 0, 0);
+}
+
+function clearPointsAndMask() {
+    // Reset state
+    isMultiMaskMode = false;
+    lastPoints = null;
+
+    // Remove points from previous mask (if any)
+    document.querySelectorAll('.icon').forEach(e => e.remove());
+
+    // Disable cut button
+    cutButton.disabled = true;
+
+    // Reset mask canvas
+    maskCanvas.getContext('2d').clearRect(0, 0, maskCanvas.width, maskCanvas.height);
+}
+clearButton.addEventListener('click', clearPointsAndMask);
+
+resetButton.addEventListener('click', () => {
+    // Update state
+    imageEmbeddings = null;
+    imageDataURI = null;
+
+    // Reset the state
+    imageInputs = null;
+    imageEmbeddings = null;
+    isDecoding = false;
+
+    // Clear points and mask (if present)
+    clearPointsAndMask();
+
+    // Update UI
+    cutButton.disabled = true;
+    imageContainer.style.backgroundImage = 'none';
+    uploadButton.style.display = 'flex';
+    statusLabel.textContent = 'Ready';
+});
+
+async function segment(data) {
+    statusLabel.textContent = 'Extracting image embedding...';
+
+    // Update state
+    imageEmbeddings = null;
+    imageDataURI = data;
+
+    // Update UI
+    imageContainer.style.backgroundImage = `url(${data})`;
+    uploadButton.style.display = 'none';
+    cutButton.disabled = true;
+
+    // Read the image and recompute image embeddings
+    const image = await RawImage.read(data);
+    imageInputs = await processor(image);
+    imageEmbeddings = await model.get_image_embeddings(imageInputs)
+
+    statusLabel.textContent = 'Embedding extracted!';
+}
+
+// Handle file selection
+fileUpload.addEventListener('change', function (e) {
+    const file = e.target.files[0];
+    if (!file) {
+        return;
+    }
+
+    const reader = new FileReader();
+
+    // Set up a callback when the file is loaded
+    reader.onload = e2 => segment(e2.target.result);
+
+    reader.readAsDataURL(file);
+});
+
+example.addEventListener('click', (e) => {
+    e.preventDefault();
+    segment(EXAMPLE_URL);
+});
+
+function addIcon({ point, label }) {
+    const icon = (label === 1 ? star : cross).cloneNode();
+    icon.style.left = `${point[0] * 100}%`;
+    icon.style.top = `${point[1] * 100}%`;
+    imageContainer.appendChild(icon);
+}
+
+// Attach hover event to image container
+imageContainer.addEventListener('mousedown', e => {
+    if (e.button !== 0 && e.button !== 2) {
+        return; // Ignore other buttons
+    }
+    if (!imageEmbeddings) {
+        return; // Ignore if not encoded yet
+    }
+    if (!isMultiMaskMode) {
+        lastPoints = [];
+        isMultiMaskMode = true;
+        cutButton.disabled = false;
+    }
+
+    const point = getPoint(e);
+    lastPoints.push(point);
+
+    // add icon
+    addIcon(point);
+
+    decode();
+});
+
+
+// Clamp a value inside a range [min, max]
+function clamp(x, min = 0, max = 1) {
+    return Math.max(Math.min(x, max), min)
+}
+
+function getPoint(e) {
+    // Get bounding box
+    const bb = imageContainer.getBoundingClientRect();
+
+    // Get the mouse coordinates relative to the container
+    const mouseX = clamp((e.clientX - bb.left) / bb.width);
+    const mouseY = clamp((e.clientY - bb.top) / bb.height);
+
+    return {
+        point: [mouseX, mouseY],
+        label: e.button === 2 // right click
+            ? 0  // negative prompt
+            : 1, // positive prompt
+    }
+}
+
+// Do not show context menu on right click
+imageContainer.addEventListener('contextmenu', e => {
+    e.preventDefault();
+});
+
+// Attach hover event to image container
+imageContainer.addEventListener('mousemove', e => {
+    if (!imageEmbeddings || isMultiMaskMode) {
+        // Ignore mousemove events if the image is not encoded yet,
+        // or we are in multi-mask mode
+        return;
+    }
+    lastPoints = [getPoint(e)];
+
+    if (!isDecoding) {
+        decode(); // Only decode if we are not already decoding
+    }
+});
+
+// Handle cut button click
+cutButton.addEventListener('click', () => {
+    const [w, h] = [maskCanvas.width, maskCanvas.height];
+
+    // Get the mask pixel data
+    const maskContext = maskCanvas.getContext('2d');
+    const maskPixelData = maskContext.getImageData(0, 0, w, h);
+
+    // Load the image
+    const image = new Image();
+    image.crossOrigin = 'anonymous';
+    image.onload = async () => {
+        // Create a new canvas to hold the image
+        const imageCanvas = new OffscreenCanvas(w, h);
+        const imageContext = imageCanvas.getContext('2d');
+        imageContext.drawImage(image, 0, 0, w, h);
+        const imagePixelData = imageContext.getImageData(0, 0, w, h);
+
+        // Create a new canvas to hold the cut-out
+        const cutCanvas = new OffscreenCanvas(w, h);
+        const cutContext = cutCanvas.getContext('2d');
+        const cutPixelData = cutContext.getImageData(0, 0, w, h);
+
+        // Copy the image pixel data to the cut canvas
+        for (let i = 3; i < maskPixelData.data.length; i += 4) {
+            if (maskPixelData.data[i] > 0) {
+                for (let j = 0; j < 4; ++j) {
+                    const offset = i - j;
+                    cutPixelData.data[offset] = imagePixelData.data[offset];
+                }
+            }
+        }
+        cutContext.putImageData(cutPixelData, 0, 0);
+
+        // Download image 
+        const link = document.createElement('a');
+        link.download = 'image.png';
+        link.href = URL.createObjectURL(await cutCanvas.convertToBlob());
+        link.click();
+        link.remove();
+    }
+    image.src = imageDataURI;
+});
+
+
+const model_id = 'Xenova/slimsam-77-uniform';
+statusLabel.textContent = 'Loading model...';
+const model = await SamModel.from_pretrained(model_id, {
+    dtype: 'fp16',
+    device: 'webgpu',
+});
+const processor = await AutoProcessor.from_pretrained(model_id);
+statusLabel.textContent = 'Ready';
+
+// Enable the user interface
+fileUpload.disabled = false;
+uploadButton.style.opacity = 1;
+example.style.pointerEvents = 'auto';