Merge branch 'main' into add-paligemma

README.md

@@ -47,7 +47,7 @@ npm i @huggingface/transformers
 Alternatively, you can use it in vanilla JS, without any bundler, by using a CDN or static hosting. For example, using [ES Modules](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules), you can import the library with:
 ```html
 <script type="module">
-    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected].0';
+    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected].1';
 </script>
 ```
 
@@ -155,7 +155,7 @@ Check out the Transformers.js [template](https://huggingface.co/new-space?templa
 
 
 
-By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models?library=transformers.js) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@huggingface/[email protected].0/dist/), which should work out-of-the-box. You can customize this as follows:
+By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models?library=transformers.js) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@huggingface/[email protected].1/dist/), which should work out-of-the-box. You can customize this as follows:
 
 ### Settings
 

docs/snippets/2_installation.snippet

@@ -7,6 +7,6 @@ npm i @huggingface/transformers
 Alternatively, you can use it in vanilla JS, without any bundler, by using a CDN or static hosting. For example, using [ES Modules](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules), you can import the library with:
 ```html
 <script type="module">
-    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected].0';
+    import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected].1';
 </script>
 ```

docs/snippets/4_custom-usage.snippet

@@ -1,6 +1,6 @@
 
 
-By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models?library=transformers.js) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@huggingface/[email protected].0/dist/), which should work out-of-the-box. You can customize this as follows:
+By default, Transformers.js uses [hosted pretrained models](https://huggingface.co/models?library=transformers.js) and [precompiled WASM binaries](https://cdn.jsdelivr.net/npm/@huggingface/[email protected].1/dist/), which should work out-of-the-box. You can customize this as follows:
 
 ### Settings
 

src/env.js

@@ -26,7 +26,7 @@ import fs from 'fs';
 import path from 'path';
 import url from 'url';
 
-const VERSION = '3.1.0';
+const VERSION = '3.1.1';
 
 // Check if various APIs are available (depends on environment)
 const IS_BROWSER_ENV = typeof window !== "undefined" && typeof window.document !== "undefined";

src/utils/image.js

@@ -303,6 +303,46 @@ export class RawImage {
         return this._update(newData, this.width, this.height, 4);
     }
 
+    /**
+     * Apply an alpha mask to the image. Operates in place.
+     * @param {RawImage} mask The mask to apply. It should have a single channel.
+     * @returns {RawImage} The masked image.
+     * @throws {Error} If the mask is not the same size as the image.
+     * @throws {Error} If the image does not have 4 channels.
+     * @throws {Error} If the mask is not a single channel.
+     */
+    putAlpha(mask) {
+        if (mask.width !== this.width || mask.height !== this.height) {
+            throw new Error(`Expected mask size to be ${this.width}x${this.height}, but got ${mask.width}x${mask.height}`);
+        }
+        if (mask.channels !== 1) {
+            throw new Error(`Expected mask to have 1 channel, but got ${mask.channels}`);
+        }
+
+        const this_data = this.data;
+        const mask_data = mask.data;
+        const num_pixels = this.width * this.height;
+        if (this.channels === 3) {
+            // Convert to RGBA and simultaneously apply mask to alpha channel
+            const newData = new Uint8ClampedArray(num_pixels * 4);
+            for (let i = 0, in_offset = 0, out_offset = 0; i < num_pixels; ++i) {
+                newData[out_offset++] = this_data[in_offset++];
+                newData[out_offset++] = this_data[in_offset++];
+                newData[out_offset++] = this_data[in_offset++];
+                newData[out_offset++] = mask_data[i];
+            }
+            return this._update(newData, this.width, this.height, 4);
+
+        } else if (this.channels === 4) {
+            // Apply mask to alpha channel in place
+            for (let i = 0; i < num_pixels; ++i) {
+                this_data[4 * i + 3] = mask_data[i];
+            }
+            return this;
+        }
+        throw new Error(`Expected image to have 3 or 4 channels, but got ${this.channels}`);
+    }
+
     /**
      * Resize the image to the given dimensions. This method uses the canvas API to perform the resizing.
      * @param {number} width The width of the new image. `null` or `-1` will preserve the aspect ratio.