Add image-feature-extractor pipeline

README.md

@@ -210,6 +210,7 @@ You can refine your search by selecting the task you're interested in (e.g., [te
 | [Token Classification](https://huggingface.co/tasks/token-classification)     | `token-classification` or `ner`  | Assigning a label to each token in a text. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TokenClassificationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=token-classification&library=transformers.js) |
 | [Translation](https://huggingface.co/tasks/translation)              |  `translation`  | Converting text from one language to another. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TranslationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=translation&library=transformers.js) |
 | [Zero-Shot Classification](https://huggingface.co/tasks/zero-shot-classification) | `zero-shot-classification`  | Classifying text into classes that are unseen during training.  | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ZeroShotClassificationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=zero-shot-classification&library=transformers.js) |
+| [Feature Extraction](https://huggingface.co/tasks/feature-extraction)         |  `feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original dataset. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.FeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=feature-extraction&library=transformers.js) |
 
 #### Vision
 
@@ -223,6 +224,7 @@ You can refine your search by selecting the task you're interested in (e.g., [te
 | [Object Detection](https://huggingface.co/tasks/object-detection)            | `object-detection`   | Identify objects of certain defined classes within an image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ObjectDetectionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=object-detection&library=transformers.js) |
 | [Video Classification](https://huggingface.co/tasks/video-classification) |  n/a  | Assigning a label or class to an entire video. | ❌ |
 | [Unconditional Image Generation](https://huggingface.co/tasks/unconditional-image-generation)      |  n/a   | Generating images with no condition in any context (like a prompt text or another image). | ❌ |
+| [Image Feature Extraction](https://huggingface.co/tasks/image-feature-extraction)         |  `image-feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageFeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=image-feature-extraction&library=transformers.js) |
 
 #### Audio
 
@@ -247,7 +249,6 @@ You can refine your search by selecting the task you're interested in (e.g., [te
 | Task                     | ID | Description | Supported? |
 |--------------------------|----|-------------|------------|
 | [Document Question Answering](https://huggingface.co/tasks/document-question-answering)         | `document-question-answering`  | Answering questions on document images. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.DocumentQuestionAnsweringPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=document-question-answering&library=transformers.js) |
-| [Feature Extraction](https://huggingface.co/tasks/feature-extraction)         |  `feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original dataset. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.FeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=feature-extraction&library=transformers.js) |
 | [Image-to-Text](https://huggingface.co/tasks/image-to-text)         |  `image-to-text`  | Output text from a given image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageToTextPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=image-to-text&library=transformers.js) |
 | [Text-to-Image](https://huggingface.co/tasks/text-to-image)         |  `text-to-image`  | Generates images from input text.  | ❌ |
 | [Visual Question Answering](https://huggingface.co/tasks/visual-question-answering)         |  `visual-question-answering`  | Answering open-ended questions based on an image. | ❌ |

docs/snippets/5_supported-tasks.snippet

@@ -17,6 +17,7 @@
 | [Token Classification](https://huggingface.co/tasks/token-classification)     | `token-classification` or `ner`  | Assigning a label to each token in a text. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TokenClassificationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=token-classification&library=transformers.js) |
 | [Translation](https://huggingface.co/tasks/translation)              |  `translation`  | Converting text from one language to another. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TranslationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=translation&library=transformers.js) |
 | [Zero-Shot Classification](https://huggingface.co/tasks/zero-shot-classification) | `zero-shot-classification`  | Classifying text into classes that are unseen during training.  | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ZeroShotClassificationPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=zero-shot-classification&library=transformers.js) |
+| [Feature Extraction](https://huggingface.co/tasks/feature-extraction)         |  `feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original dataset. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.FeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=feature-extraction&library=transformers.js) |
 
 #### Vision
 
@@ -30,6 +31,7 @@
 | [Object Detection](https://huggingface.co/tasks/object-detection)            | `object-detection`   | Identify objects of certain defined classes within an image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ObjectDetectionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=object-detection&library=transformers.js) |
 | [Video Classification](https://huggingface.co/tasks/video-classification) |  n/a  | Assigning a label or class to an entire video. | ❌ |
 | [Unconditional Image Generation](https://huggingface.co/tasks/unconditional-image-generation)      |  n/a   | Generating images with no condition in any context (like a prompt text or another image). | ❌ |
+| [Image Feature Extraction](https://huggingface.co/tasks/image-feature-extraction)         |  `image-feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageFeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=image-feature-extraction&library=transformers.js) |
 
 #### Audio
 
@@ -54,7 +56,6 @@
 | Task                     | ID | Description | Supported? |
 |--------------------------|----|-------------|------------|
 | [Document Question Answering](https://huggingface.co/tasks/document-question-answering)         | `document-question-answering`  | Answering questions on document images. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.DocumentQuestionAnsweringPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=document-question-answering&library=transformers.js) |
-| [Feature Extraction](https://huggingface.co/tasks/feature-extraction)         |  `feature-extraction`  | Transforming raw data into numerical features that can be processed while preserving the information in the original dataset. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.FeatureExtractionPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=feature-extraction&library=transformers.js) |
 | [Image-to-Text](https://huggingface.co/tasks/image-to-text)         |  `image-to-text`  | Output text from a given image. | ✅ [(docs)](https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageToTextPipeline)<br>[(models)](https://huggingface.co/models?pipeline_tag=image-to-text&library=transformers.js) |
 | [Text-to-Image](https://huggingface.co/tasks/text-to-image)         |  `text-to-image`  | Generates images from input text.  | ❌ |
 | [Visual Question Answering](https://huggingface.co/tasks/visual-question-answering)         |  `visual-question-answering`  | Answering open-ended questions based on an image. | ❌ |

src/models.js

@@ -5800,6 +5800,12 @@ const MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES = new Map([
     ['glpn', ['GLPNForDepthEstimation', GLPNForDepthEstimation]],
 ])
 
+// NOTE: This is custom to Transformers.js, and is necessary because certain models
+// (e.g., CLIP) are split into vision and text components
+const MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES = new Map([
+    ['clip', ['CLIPVisionModelWithProjection', CLIPVisionModelWithProjection]],
+    ['siglip', ['SiglipVisionModel', SiglipVisionModel]],
+])
 
 const MODEL_CLASS_TYPE_MAPPING = [
     [MODEL_MAPPING_NAMES_ENCODER_ONLY, MODEL_TYPES.EncoderOnly],
@@ -5828,6 +5834,9 @@ const MODEL_CLASS_TYPE_MAPPING = [
     [MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES, MODEL_TYPES.EncoderOnly],
     [MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES, MODEL_TYPES.EncoderOnly],
     [MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES, MODEL_TYPES.EncoderOnly],
+
+    // Custom:
+    [MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES, MODEL_TYPES.EncoderOnly],
 ];
 
 for (const [mappings, type] of MODEL_CLASS_TYPE_MAPPING) {
@@ -5841,9 +5850,7 @@ for (const [mappings, type] of MODEL_CLASS_TYPE_MAPPING) {
 
 const CUSTOM_MAPPING = [
     ['CLIPTextModelWithProjection', CLIPTextModelWithProjection, MODEL_TYPES.EncoderOnly],
-    ['CLIPVisionModelWithProjection', CLIPVisionModelWithProjection, MODEL_TYPES.EncoderOnly],
     ['SiglipTextModel', SiglipTextModel, MODEL_TYPES.EncoderOnly],
-    ['SiglipVisionModel', SiglipVisionModel, MODEL_TYPES.EncoderOnly],
     ['ClapTextModelWithProjection', ClapTextModelWithProjection, MODEL_TYPES.EncoderOnly],
     ['ClapAudioModelWithProjection', ClapAudioModelWithProjection, MODEL_TYPES.EncoderOnly],
 ]
@@ -6070,6 +6077,10 @@ export class AutoModelForDepthEstimation extends PretrainedMixin {
     static MODEL_CLASS_MAPPINGS = [MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES];
 }
 
+export class AutoModelForImageFeatureExtraction extends PretrainedMixin {
+    static MODEL_CLASS_MAPPINGS = [MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES];
+}
+
 //////////////////////////////////////////////////
 
 //////////////////////////////////////////////////

src/pipelines.js

@@ -39,6 +39,7 @@ import {
     AutoModelForDocumentQuestionAnswering,
     AutoModelForImageToImage,
     AutoModelForDepthEstimation,
+    AutoModelForImageFeatureExtraction,
     PreTrainedModel,
 } from './models.js';
 import {
@@ -1206,6 +1207,82 @@ export class FeatureExtractionPipeline extends (/** @type {new (options: TextPip
     }
 }
 
+
+/**
+ * @typedef {Object} ImageFeatureExtractionPipelineOptions Parameters specific to image feature extraction pipelines.
+ * @property {boolean} [pool=null] Whether or not to return the pooled output. If set to `false`, the model will return the raw hidden states.
+ * 
+ * @callback ImageFeatureExtractionPipelineCallback Extract the features of the input(s).
+ * @param {ImagePipelineInputs} images One or several images (or one list of images) to get the features of.
+ * @param {ImageFeatureExtractionPipelineOptions} [options] The options to use for image feature extraction.
+ * @returns {Promise<Tensor>} The image features computed by the model.
+ * 
+ * @typedef {ImagePipelineConstructorArgs & ImageFeatureExtractionPipelineCallback & Disposable} ImageFeatureExtractionPipelineType
+ */
+
+/**
+ * Image feature extraction pipeline using no model head. This pipeline extracts the hidden
+ * states from the base transformer, which can be used as features in downstream tasks.
+ * 
+ * **Example:** Perform image feature extraction with `Xenova/vit-base-patch16-224-in21k`.
+ * ```javascript
+ * const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/vit-base-patch16-224-in21k');
+ * const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
+ * const features = await image_feature_extractor(url);
+ * // Tensor {
+ * //   dims: [ 1, 197, 768 ],
+ * //   type: 'float32',
+ * //   data: Float32Array(151296) [ ... ],
+ * //   size: 151296
+ * // }
+ * ```
+ * 
+ * **Example:** Compute image embeddings with `Xenova/clip-vit-base-patch32`.
+ * ```javascript
+ * const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/clip-vit-base-patch32');
+ * const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
+ * const features = await image_feature_extractor(url);
+ * // Tensor {
+ * //   dims: [ 1, 512 ],
+ * //   type: 'float32',
+ * //   data: Float32Array(512) [ ... ],
+ * //   size: 512
+ * // }
+ * ```
+ */
+export class ImageFeatureExtractionPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ImageFeatureExtractionPipelineType} */ (Pipeline)) {
+    /**
+     * Create a new ImageFeatureExtractionPipeline.
+     * @param {ImagePipelineConstructorArgs} options An object used to instantiate the pipeline.
+     */
+    constructor(options) {
+        super(options);
+    }
+
+    /** @type {ImageFeatureExtractionPipelineCallback} */
+    async _call(images, {
+        pool = null,
+    } = {}) {
+
+        const preparedImages = await prepareImages(images);
+        const { pixel_values } = await this.processor(preparedImages);
+        const outputs = await this.model({ pixel_values });
+
+        /** @type {Tensor} */
+        let result;
+        if (pool) {
+            if (!('pooler_output' in outputs)) {
+                throw Error(`No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.`);
+            }
+            result = outputs.pooler_output;
+
+        } else {
+            result = outputs.last_hidden_state ?? outputs.logits ?? outputs.image_embeds;
+        }
+        return result;
+    }
+}
+
 // TODO
 // export class SentenceSimilarityPipeline extends Pipeline {
 // }
@@ -2953,6 +3030,17 @@ const SUPPORTED_TASKS = Object.freeze({
         },
         "type": "text",
     },
+    "image-feature-extraction": {
+        "processor": AutoProcessor,
+        "pipeline": ImageFeatureExtractionPipeline,
+        "model": [AutoModelForImageFeatureExtraction, AutoModel],
+        "default": {
+            // TODO: replace with original
+            // "model": "google/vit-base-patch16-224",
+            "model": "Xenova/vit-base-patch16-224-in21k",
+        },
+        "type": "image",
+    },
 })