@huggingface/transformers
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State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
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JavaScript
import { PreTrainedModel } from '../modeling_utils.js';
import { ModelOutput } from '../modeling_outputs.js';
import { Tensor } from '../../utils/tensor.js';
export class RTDetrPreTrainedModel extends PreTrainedModel {}
export class RTDetrModel extends RTDetrPreTrainedModel {}
export class RTDetrForObjectDetection extends RTDetrPreTrainedModel {
/**
* @param {any} model_inputs
*/
async _call(model_inputs) {
return new RTDetrObjectDetectionOutput(await super._call(model_inputs));
}
}
export class RTDetrObjectDetectionOutput extends ModelOutput {
/**
* @param {Object} output The output of the model.
* @param {Tensor} output.logits Classification logits (including no-object) for all queries.
* @param {Tensor} output.pred_boxes Normalized boxes coordinates for all queries, represented as (center_x, center_y, width, height).
* These values are normalized in [0, 1], relative to the size of each individual image in the batch (disregarding possible padding).
*/
constructor({ logits, pred_boxes }) {
super();
this.logits = logits;
this.pred_boxes = pred_boxes;
}
}