rebuild types

.build.json

@@ -6,7 +6,7 @@
     "output": "build.log"
   },
   "profiles": {
-    "production": ["compile", "typedoc", "lint", "changelog"],
+    "production": ["compile", "typings", "typedoc", "lint", "changelog"],
     "development": ["serve", "watch", "compile"]
   },
   "clean": {

CHANGELOG.md

@@ -9,6 +9,9 @@
   
 ## Changelog
   
+### **HEAD -> master** 2024/01/17 mandic00@live.com
+
+
 ### **1.7.13** 2024/01/17 mandic00@live.com
 
 

package.json

@@ -22,8 +22,9 @@
   },
   "scripts": {
     "start": "node --no-warnings demo/node.js",
-    "dev": "build --profile development",
     "build": "node build.js",
+    "dev": "build --profile development",
+    "typings": "build --profile typings",
     "lint": "eslint src/ demo/",
     "test": "node --trace-warnings test/test-node.js",
     "scan": "npx auditjs@latest ossi --dev --quiet"

types/face-api.d.ts

@@ -1,4 +1,5 @@
 /// <reference path="../src/types/webgpu.d.ts" />
+/// <reference types="node" />
 
 declare const add: typeof add_;
 
@@ -1221,7 +1222,7 @@ export declare function extractFaces(input: TNetInput, detections: Array<FaceDet
  */
 export declare function extractFaceTensors(imageTensor: tf.Tensor3D | tf.Tensor4D, detections: Array<FaceDetection | Rect>): Promise<tf.Tensor3D[]>;
 
-export declare const FACE_EXPRESSION_LABELS: string[];
+export declare const FACE_EXPRESSION_LABELS: readonly ["neutral", "happy", "sad", "angry", "fearful", "disgusted", "surprised"];
 
 export declare class FaceDetection extends ObjectDetection implements IFaceDetecion {
     constructor(score: number, relativeBox: Rect, imageDims: IDimensions);
@@ -1239,7 +1240,7 @@ export declare class FaceExpressionNet extends FaceProcessor<FaceFeatureExtracto
     constructor(faceFeatureExtractor?: FaceFeatureExtractor);
     forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D;
     forward(input: TNetInput): Promise<tf.Tensor2D>;
-    predictExpressions(input: TNetInput): Promise<any>;
+    predictExpressions(input: TNetInput): Promise<FaceExpressions | FaceExpressions[]>;
     protected getDefaultModelName(): string;
     protected getClassifierChannelsIn(): number;
     protected getClassifierChannelsOut(): number;
@@ -1255,7 +1256,7 @@ export declare class FaceExpressions {
     surprised: number;
     constructor(probabilities: number[] | Float32Array);
     asSortedArray(): {
-        expression: string;
+        expression: "neutral" | "happy" | "sad" | "angry" | "fearful" | "disgusted" | "surprised";
         probability: number;
     }[];
 }
@@ -1431,7 +1432,7 @@ export declare function fetchOrThrow(url: string, init?: RequestInit): Promise<R
 export declare function fetchVideo(uri: string): Promise<HTMLVideoElement>;
 
 declare type FileSystem_2 = {
-    readFile: (filePath: string) => Promise<any>;
+    readFile: (filePath: string) => Promise<string | Buffer>;
 };
 export { FileSystem_2 as FileSystem }
 
@@ -2113,6 +2114,12 @@ declare function loadWeights(manifest: WeightsManifestConfig, filePathPrefix?: s
 
 export declare const locateFaces: (input: TNetInput, options: SsdMobilenetv1Options) => Promise<FaceDetection[]>;
 
+declare type MainBlockParams = {
+    separable_conv0: SeparableConvParams;
+    separable_conv1: SeparableConvParams;
+    separable_conv2: SeparableConvParams;
+};
+
 export declare function matchDimensions(input: IDimensions, reference: IDimensions, useMediaDimensions?: boolean): {
     width: number;
     height: number;
@@ -2616,15 +2623,15 @@ export declare abstract class NeuralNetwork<TNetParams> {
     reassignParamFromPath(paramPath: string, tensor: tf.Tensor): void;
     getParamList(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     getTrainableParams(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     getFrozenParams(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     variable(): void;
     freeze(): void;
@@ -2834,8 +2841,8 @@ export declare const predictAgeAndGender: (input: TNetInput) => Promise<AgeAndGe
 declare class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    protected extractedFaces?: any[] | undefined;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: any[] | undefined);
+    protected extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined);
 }
 
 declare class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {
@@ -2870,8 +2877,8 @@ export declare class PredictedBox extends LabeledBox {
 declare class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    protected extractedFaces?: any[] | undefined;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: any[] | undefined);
+    protected extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined);
 }
 
 declare type PredictionLayerParams = {
@@ -3316,8 +3323,14 @@ declare function softmax_<T extends Tensor>(logits: T | TensorLike, dim?: number
 
 export declare class SsdMobilenetv1 extends NeuralNetwork<NetParams_4> {
     constructor();
-    forwardInput(input: NetInput): any;
-    forward(input: TNetInput): Promise<any>;
+    forwardInput(input: NetInput): {
+        boxes: tf.Tensor2D[];
+        scores: tf.Tensor1D[];
+    };
+    forward(input: TNetInput): Promise<{
+        boxes: tf.Tensor2D[];
+        scores: tf.Tensor1D[];
+    }>;
     locateFaces(input: TNetInput, options?: ISsdMobilenetv1Options): Promise<FaceDetection[]>;
     protected getDefaultModelName(): string;
     protected extractParamsFromWeightMap(weightMap: tf.NamedTensorMap): {
@@ -4116,7 +4129,7 @@ declare type TinyXceptionParams = {
         reduction_block_0: ReductionBlockParams;
         reduction_block_1: ReductionBlockParams;
     };
-    middle_flow: any;
+    middle_flow: Record<`main_block_${number}`, MainBlockParams>;
     exit_flow: {
         reduction_block: ReductionBlockParams;
         separable_conv: SeparableConvParams;
@@ -4165,7 +4178,7 @@ declare class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
         params: TinyYolov2NetParams;
         paramMappings: ParamMapping[];
     };
-    protected extractBoxes(outputTensor: tf.Tensor4D, inputBlobDimensions: Dimensions, scoreThreshold?: number): Promise<any>;
+    protected extractBoxes(outputTensor: tf.Tensor4D, inputBlobDimensions: Dimensions, scoreThreshold?: number): Promise<TinyYolov2ExtractBoxesResult[]>;
     private extractPredictedClass;
 }
 
@@ -4180,6 +4193,16 @@ export declare type TinyYolov2Config = {
     isFirstLayerConv2d?: boolean;
 };
 
+export declare type TinyYolov2ExtractBoxesResult = {
+    box: BoundingBox;
+    score: number;
+    classScore: number;
+    label: number;
+    row: number;
+    col: number;
+    anchor: number;
+};
+
 export declare type TinyYolov2NetParams = DefaultTinyYolov2NetParams | MobilenetParams;
 
 export declare class TinyYolov2Options {

types/lib/src/NeuralNetwork.d.ts

@@ -12,15 +12,15 @@ export declare abstract class NeuralNetwork<TNetParams> {
     reassignParamFromPath(paramPath: string, tensor: tf.Tensor): void;
     getParamList(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     getTrainableParams(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     getFrozenParams(): {
         path: string;
-        tensor: tf.Tensor;
+        tensor: tf.Tensor<tf.Rank>;
     }[];
     variable(): void;
     freeze(): void;

types/lib/src/env/types.d.ts

@@ -1,5 +1,6 @@
+/// <reference types="node" />
 export type FileSystem = {
-    readFile: (filePath: string) => Promise<any>;
+    readFile: (filePath: string) => Promise<string | Buffer>;
 };
 export type Environment = FileSystem & {
     Canvas: typeof HTMLCanvasElement;

types/lib/src/faceExpressionNet/FaceExpressionNet.d.ts

@@ -3,11 +3,12 @@ import { NetInput, TNetInput } from '../dom/index';
 import { FaceFeatureExtractor } from '../faceFeatureExtractor/FaceFeatureExtractor';
 import { FaceFeatureExtractorParams } from '../faceFeatureExtractor/types';
 import { FaceProcessor } from '../faceProcessor/FaceProcessor';
+import { FaceExpressions } from './FaceExpressions';
 export declare class FaceExpressionNet extends FaceProcessor<FaceFeatureExtractorParams> {
     constructor(faceFeatureExtractor?: FaceFeatureExtractor);
     forwardInput(input: NetInput | tf.Tensor4D): tf.Tensor2D;
     forward(input: TNetInput): Promise<tf.Tensor2D>;
-    predictExpressions(input: TNetInput): Promise<any>;
+    predictExpressions(input: TNetInput): Promise<FaceExpressions | FaceExpressions[]>;
     protected getDefaultModelName(): string;
     protected getClassifierChannelsIn(): number;
     protected getClassifierChannelsOut(): number;

types/lib/src/faceExpressionNet/FaceExpressions.d.ts

@@ -1,4 +1,4 @@
-export declare const FACE_EXPRESSION_LABELS: string[];
+export declare const FACE_EXPRESSION_LABELS: readonly ["neutral", "happy", "sad", "angry", "fearful", "disgusted", "surprised"];
 export declare class FaceExpressions {
     neutral: number;
     happy: number;
@@ -9,7 +9,7 @@ export declare class FaceExpressions {
     surprised: number;
     constructor(probabilities: number[] | Float32Array);
     asSortedArray(): {
-        expression: string;
+        expression: "neutral" | "happy" | "sad" | "angry" | "fearful" | "disgusted" | "surprised";
         probability: number;
     }[];
 }

types/lib/src/globalApi/PredictAgeAndGenderTask.d.ts

@@ -1,3 +1,4 @@
+import * as tf from '../../dist/tfjs.esm';
 import { TNetInput } from '../dom/index';
 import { WithAge } from '../factories/WithAge';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
@@ -9,8 +10,8 @@ import { PredictAllFaceExpressionsTask, PredictAllFaceExpressionsWithFaceAlignme
 export declare class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    protected extractedFaces?: any[] | undefined;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: any[] | undefined);
+    protected extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined);
 }
 export declare class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {
     run(): Promise<WithAge<WithGender<TSource>>[]>;

types/lib/src/globalApi/PredictFaceExpressionsTask.d.ts

@@ -1,3 +1,4 @@
+import * as tf from '../../dist/tfjs.esm';
 import { TNetInput } from '../dom/index';
 import { WithFaceDetection } from '../factories/WithFaceDetection';
 import { WithFaceExpressions } from '../factories/WithFaceExpressions';
@@ -8,8 +9,8 @@ import { PredictAllAgeAndGenderTask, PredictAllAgeAndGenderWithFaceAlignmentTask
 export declare class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends ComposableTask<TReturn> {
     protected parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>;
     protected input: TNetInput;
-    protected extractedFaces?: any[] | undefined;
-    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: any[] | undefined);
+    protected extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined;
+    constructor(parentTask: ComposableTask<TParentReturn> | Promise<TParentReturn>, input: TNetInput, extractedFaces?: (tf.Tensor3D | HTMLCanvasElement)[] | undefined);
 }
 export declare class PredictAllFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {
     run(): Promise<WithFaceExpressions<TSource>[]>;

types/lib/src/ssdMobilenetv1/SsdMobilenetv1.d.ts

@@ -6,8 +6,14 @@ import { ISsdMobilenetv1Options } from './SsdMobilenetv1Options';
 import { NetParams } from './types';
 export declare class SsdMobilenetv1 extends NeuralNetwork<NetParams> {
     constructor();
-    forwardInput(input: NetInput): any;
-    forward(input: TNetInput): Promise<any>;
+    forwardInput(input: NetInput): {
+        boxes: tf.Tensor2D[];
+        scores: tf.Tensor1D[];
+    };
+    forward(input: TNetInput): Promise<{
+        boxes: tf.Tensor2D[];
+        scores: tf.Tensor1D[];
+    }>;
     locateFaces(input: TNetInput, options?: ISsdMobilenetv1Options): Promise<FaceDetection[]>;
     protected getDefaultModelName(): string;
     protected extractParamsFromWeightMap(weightMap: tf.NamedTensorMap): {

types/lib/src/ssdMobilenetv1/boxPredictionLayer.d.ts

@@ -1,3 +1,6 @@
 import * as tf from '../../dist/tfjs.esm';
 import { BoxPredictionParams } from './types';
-export declare function boxPredictionLayer(x: tf.Tensor4D, params: BoxPredictionParams): any;
+export declare function boxPredictionLayer(x: tf.Tensor4D, params: BoxPredictionParams): {
+    boxPredictionEncoding: tf.Tensor<tf.Rank>;
+    classPrediction: tf.Tensor<tf.Rank>;
+};

types/lib/src/ssdMobilenetv1/mobileNetV1.d.ts

@@ -1,3 +1,6 @@
 import * as tf from '../../dist/tfjs.esm';
 import { MobileNetV1 } from './types';
-export declare function mobileNetV1(x: tf.Tensor4D, params: MobileNetV1.Params): any;
+export declare function mobileNetV1(x: tf.Tensor4D, params: MobileNetV1.Params): {
+    out: tf.Tensor4D;
+    conv11: any;
+};

types/lib/src/ssdMobilenetv1/outputLayer.d.ts

@@ -1,3 +1,6 @@
 import * as tf from '../../dist/tfjs.esm';
 import { OutputLayerParams } from './types';
-export declare function outputLayer(boxPredictions: tf.Tensor4D, classPredictions: tf.Tensor4D, params: OutputLayerParams): any;
+export declare function outputLayer(boxPredictions: tf.Tensor4D, classPredictions: tf.Tensor4D, params: OutputLayerParams): {
+    boxes: tf.Tensor2D[];
+    scores: tf.Tensor1D[];
+};

types/lib/src/ssdMobilenetv1/pointwiseConvLayer.d.ts

@@ -1,3 +1,3 @@
 import * as tf from '../../dist/tfjs.esm';
 import { PointwiseConvParams } from './types';
-export declare function pointwiseConvLayer(x: tf.Tensor4D, params: PointwiseConvParams, strides: [number, number]): any;
+export declare function pointwiseConvLayer(x: tf.Tensor4D, params: PointwiseConvParams, strides: [number, number]): tf.Tensor4D;

types/lib/src/ssdMobilenetv1/predictionLayer.d.ts

@@ -1,3 +1,6 @@
 import * as tf from '../../dist/tfjs.esm';
 import { PredictionLayerParams } from './types';
-export declare function predictionLayer(x: tf.Tensor4D, conv11: tf.Tensor4D, params: PredictionLayerParams): any;
+export declare function predictionLayer(x: tf.Tensor4D, conv11: tf.Tensor4D, params: PredictionLayerParams): {
+    boxPredictions: tf.Tensor4D;
+    classPredictions: tf.Tensor4D;
+};

types/lib/src/tinyYolov2/TinyYolov2Base.d.ts

@@ -6,7 +6,7 @@ import { TNetInput } from '../dom/types';
 import { NeuralNetwork } from '../NeuralNetwork';
 import { TinyYolov2Config } from './config';
 import { ITinyYolov2Options } from './TinyYolov2Options';
-import { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2NetParams } from './types';
+import { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2ExtractBoxesResult, TinyYolov2NetParams } from './types';
 export declare class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
     static DEFAULT_FILTER_SIZES: number[];
     private _config;
@@ -28,6 +28,6 @@ export declare class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
         params: TinyYolov2NetParams;
         paramMappings: import("../common/types").ParamMapping[];
     };
-    protected extractBoxes(outputTensor: tf.Tensor4D, inputBlobDimensions: Dimensions, scoreThreshold?: number): Promise<any>;
+    protected extractBoxes(outputTensor: tf.Tensor4D, inputBlobDimensions: Dimensions, scoreThreshold?: number): Promise<TinyYolov2ExtractBoxesResult[]>;
     private extractPredictedClass;
 }

types/lib/src/tinyYolov2/types.d.ts

@@ -1,4 +1,5 @@
 import * as tf from '../../dist/tfjs.esm';
+import { BoundingBox } from '../classes';
 import { ConvParams } from '../common/index';
 import { SeparableConvParams } from '../common/types';
 export type BatchNorm = {
@@ -32,3 +33,12 @@ export type DefaultTinyYolov2NetParams = {
     conv8: ConvParams;
 };
 export type TinyYolov2NetParams = DefaultTinyYolov2NetParams | MobilenetParams;
+export type TinyYolov2ExtractBoxesResult = {
+    box: BoundingBox;
+    score: number;
+    classScore: number;
+    label: number;
+    row: number;
+    col: number;
+    anchor: number;
+};

types/lib/src/xception/types.d.ts

@@ -15,7 +15,7 @@ export type TinyXceptionParams = {
         reduction_block_0: ReductionBlockParams;
         reduction_block_1: ReductionBlockParams;
     };
-    middle_flow: any;
+    middle_flow: Record<`main_block_${number}`, MainBlockParams>;
     exit_flow: {
         reduction_block: ReductionBlockParams;
         separable_conv: SeparableConvParams;