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import {
ImageProcessor,
post_process_object_detection,
post_process_panoptic_segmentation,
post_process_instance_segmentation,
} from "../../base/image_processors_utils.js";
import { full } from '../../utils/tensor.js';
/**
* @typedef {object} DetrFeatureExtractorResultProps
* @property {import('../../utils/tensor.js').Tensor} pixel_mask
* @typedef {import('../../base/image_processors_utils.js').ImageProcessorResult & DetrFeatureExtractorResultProps} DetrFeatureExtractorResult
*/
export class DetrImageProcessor extends ImageProcessor {
/**
* Calls the feature extraction process on an array of images, preprocesses
* each image, and concatenates the resulting features into a single Tensor.
* @param {import('../../utils/image.js').RawImage[]} images The image(s) to extract features from.
* @returns {Promise<DetrFeatureExtractorResult>} An object containing the concatenated pixel values of the preprocessed images.
*/
async _call(images) {
const result = await super._call(images);
// TODO support differently-sized images, for now assume all images are the same size.
// TODO support different mask sizes (not just 64x64)
// Currently, just fill pixel mask with 1s
const maskSize = [result.pixel_values.dims[0], 64, 64];
const pixel_mask = full(maskSize, 1n);
return { ...result, pixel_mask };
}
/** @type {typeof post_process_object_detection} */
post_process_object_detection(...args) {
return post_process_object_detection(...args);
}
/** @type {typeof post_process_panoptic_segmentation} */
post_process_panoptic_segmentation(...args) {
return post_process_panoptic_segmentation(...args);
}
/** @type {typeof post_process_instance_segmentation} */
post_process_instance_segmentation(...args) {
return post_process_instance_segmentation(...args);
}
}
export class DetrFeatureExtractor extends DetrImageProcessor { } // NOTE: extends DetrImageProcessor
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