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import { IMAGE_PROCESSOR_NAME } from '../../utils/constants.js';
import { getModelJSON } from '../../utils/hub.js';
import { Processor } from '../../base/processing_utils.js';
import * as AllProcessors from '../processors.js';
import * as AllImageProcessors from '../image_processors.js';
import * as AllFeatureExtractors from '../feature_extractors.js';
/**
* Helper class which is used to instantiate pretrained processors with the `from_pretrained` function.
* The chosen processor class is determined by the type specified in the processor config.
*
* **Example:** Load a processor using `from_pretrained`.
* ```javascript
* let processor = await AutoProcessor.from_pretrained('openai/whisper-tiny.en');
* ```
*
* **Example:** Run an image through a processor.
* ```javascript
* let processor = await AutoProcessor.from_pretrained('Xenova/clip-vit-base-patch16');
* let image = await RawImage.read('https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/football-match.jpg');
* let image_inputs = await processor(image);
* // {
* // "pixel_values": {
* // "dims": [ 1, 3, 224, 224 ],
* // "type": "float32",
* // "data": Float32Array [ -1.558687686920166, -1.558687686920166, -1.5440893173217773, ... ],
* // "size": 150528
* // },
* // "original_sizes": [
* // [ 533, 800 ]
* // ],
* // "reshaped_input_sizes": [
* // [ 224, 224 ]
* // ]
* // }
* ```
*/
export class AutoProcessor {
/** @type {typeof Processor.from_pretrained} */
static async from_pretrained(pretrained_model_name_or_path, options={}) {
// TODO: first check for processor.json
const preprocessorConfig = await getModelJSON(pretrained_model_name_or_path, IMAGE_PROCESSOR_NAME, true, options);
const { image_processor_type, feature_extractor_type, processor_class } = preprocessorConfig;
if (processor_class && AllProcessors[processor_class]) {
return AllProcessors[processor_class].from_pretrained(pretrained_model_name_or_path, options);
}
if (!image_processor_type && !feature_extractor_type) {
throw new Error('No `image_processor_type` or `feature_extractor_type` found in the config.');
}
const components = {};
if (image_processor_type) {
// Some image processors are saved with the "Fast" suffix, so we remove that if present.
const image_processor_class = AllImageProcessors[image_processor_type.replace(/Fast$/, '')];
if (!image_processor_class) {
throw new Error(`Unknown image_processor_type: '${image_processor_type}'.`);
}
components.image_processor = new image_processor_class(preprocessorConfig);
}
if (feature_extractor_type) {
const image_processor_class = AllImageProcessors[feature_extractor_type];
if (image_processor_class) {
// Handle legacy case where image processors were specified as feature extractors
components.image_processor = new image_processor_class(preprocessorConfig);
} else {
const feature_extractor_class = AllFeatureExtractors[feature_extractor_type];
if (!feature_extractor_class) {
throw new Error(`Unknown feature_extractor_type: '${feature_extractor_type}'.`);
}
components.feature_extractor = new feature_extractor_class(preprocessorConfig);
}
}
const config = {};
return new Processor(config, components, null);
}
}
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