strong typings

dist/demo-browser-index.js

@@ -78244,7 +78244,9 @@ function enhance(input2) {
   const image3 = tidy(() => {
     const box3 = [[0.05, 0.15, 0.85, 0.85]];
     const tensor2 = input2.image || input2.tensor;
-    const crop = tensor2.shape.length === 3 ? image.cropAndResize(tensor2.expandDims(0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
+    if (!(tensor2 instanceof Tensor))
+      return null;
+    const crop = tensor2.shape.length === 3 ? image.cropAndResize(expandDims(tensor2, 0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
     const rgb3 = [0.2989, 0.587, 0.114];
     const [red, green, blue] = split(crop, 3, 3);
     const redNorm = mul(red, rgb3[0]);
@@ -99184,7 +99186,7 @@ var Human = class {
         return null;
       if (!input2)
         return "input is not defined";
-      if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof this.tf.Tensor)) {
+      if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof Tensor)) {
         return "input must be a tensor";
       }
       try {
@@ -99236,7 +99238,7 @@ var Human = class {
     });
     _calculateFaceAngle.set(this, (mesh) => {
       if (!mesh || mesh.length < 300)
-        return {};
+        return {roll: null, yaw: null, pitch: null};
       const radians = (a12, a22, b1, b2) => Math.atan2(b2 - a22, b1 - a12);
       const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
       const angle = {

dist/human.esm-nobundle.js

@@ -4396,7 +4396,9 @@ function enhance(input) {
   const image13 = tf8.tidy(() => {
     const box3 = [[0.05, 0.15, 0.85, 0.85]];
     const tensor = input.image || input.tensor;
-    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tensor.expandDims(0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
+    if (!(tensor instanceof tf8.Tensor))
+      return null;
+    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tf8.expandDims(tensor, 0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
     const rgb3 = [0.2989, 0.587, 0.114];
     const [red, green, blue] = tf8.split(crop, 3, 3);
     const redNorm = tf8.mul(red, rgb3[0]);
@@ -25351,7 +25353,7 @@ var Human = class {
         return null;
       if (!input)
         return "input is not defined";
-      if (this.tf.ENV.flags.IS_NODE && !(input instanceof this.tf.Tensor)) {
+      if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf18.Tensor)) {
         return "input must be a tensor";
       }
       try {
@@ -25403,7 +25405,7 @@ var Human = class {
     });
     _calculateFaceAngle.set(this, (mesh) => {
       if (!mesh || mesh.length < 300)
-        return {};
+        return {roll: null, yaw: null, pitch: null};
       const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
       const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
       const angle = {

dist/human.esm.js

@@ -78244,7 +78244,9 @@ function enhance(input2) {
   const image3 = tidy(() => {
     const box3 = [[0.05, 0.15, 0.85, 0.85]];
     const tensor2 = input2.image || input2.tensor;
-    const crop = tensor2.shape.length === 3 ? image.cropAndResize(tensor2.expandDims(0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
+    if (!(tensor2 instanceof Tensor))
+      return null;
+    const crop = tensor2.shape.length === 3 ? image.cropAndResize(expandDims(tensor2, 0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
     const rgb3 = [0.2989, 0.587, 0.114];
     const [red, green, blue] = split(crop, 3, 3);
     const redNorm = mul(red, rgb3[0]);
@@ -99184,7 +99186,7 @@ var Human = class {
         return null;
       if (!input2)
         return "input is not defined";
-      if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof this.tf.Tensor)) {
+      if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof Tensor)) {
         return "input must be a tensor";
       }
       try {
@@ -99236,7 +99238,7 @@ var Human = class {
     });
     _calculateFaceAngle.set(this, (mesh) => {
       if (!mesh || mesh.length < 300)
-        return {};
+        return {roll: null, yaw: null, pitch: null};
       const radians = (a12, a22, b1, b2) => Math.atan2(b2 - a22, b1 - a12);
       const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
       const angle = {

dist/human.js

@@ -78251,7 +78251,9 @@ return a / b;`;
     const image3 = tidy(() => {
       const box3 = [[0.05, 0.15, 0.85, 0.85]];
       const tensor2 = input2.image || input2.tensor;
-      const crop = tensor2.shape.length === 3 ? image.cropAndResize(tensor2.expandDims(0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
+      if (!(tensor2 instanceof Tensor))
+        return null;
+      const crop = tensor2.shape.length === 3 ? image.cropAndResize(expandDims(tensor2, 0), box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]) : image.cropAndResize(tensor2, box3, [0], [model5.inputs[0].shape[2], model5.inputs[0].shape[1]]);
       const rgb3 = [0.2989, 0.587, 0.114];
       const [red, green, blue] = split(crop, 3, 3);
       const redNorm = mul(red, rgb3[0]);
@@ -99191,7 +99193,7 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
           return null;
         if (!input2)
           return "input is not defined";
-        if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof this.tf.Tensor)) {
+        if (this.tf.ENV.flags.IS_NODE && !(input2 instanceof Tensor)) {
           return "input must be a tensor";
         }
         try {
@@ -99243,7 +99245,7 @@ lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
       });
       _calculateFaceAngle.set(this, (mesh) => {
         if (!mesh || mesh.length < 300)
-          return {};
+          return {roll: null, yaw: null, pitch: null};
         const radians = (a12, a22, b1, b2) => Math.atan2(b2 - a22, b1 - a12);
         const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
         const angle = {

dist/human.node-gpu.js

@@ -4376,7 +4376,9 @@ function enhance(input) {
   const image13 = tf8.tidy(() => {
     const box3 = [[0.05, 0.15, 0.85, 0.85]];
     const tensor = input.image || input.tensor;
-    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tensor.expandDims(0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
+    if (!(tensor instanceof tf8.Tensor))
+      return null;
+    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tf8.expandDims(tensor, 0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
     const rgb3 = [0.2989, 0.587, 0.114];
     const [red, green, blue] = tf8.split(crop, 3, 3);
     const redNorm = tf8.mul(red, rgb3[0]);
@@ -25331,7 +25333,7 @@ var Human = class {
         return null;
       if (!input)
         return "input is not defined";
-      if (this.tf.ENV.flags.IS_NODE && !(input instanceof this.tf.Tensor)) {
+      if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf18.Tensor)) {
         return "input must be a tensor";
       }
       try {
@@ -25383,7 +25385,7 @@ var Human = class {
     });
     _calculateFaceAngle.set(this, (mesh) => {
       if (!mesh || mesh.length < 300)
-        return {};
+        return {roll: null, yaw: null, pitch: null};
       const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
       const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
       const angle = {

dist/human.node.js

@@ -4376,7 +4376,9 @@ function enhance(input) {
   const image13 = tf8.tidy(() => {
     const box3 = [[0.05, 0.15, 0.85, 0.85]];
     const tensor = input.image || input.tensor;
-    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tensor.expandDims(0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
+    if (!(tensor instanceof tf8.Tensor))
+      return null;
+    const crop = tensor.shape.length === 3 ? tf8.image.cropAndResize(tf8.expandDims(tensor, 0), box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]) : tf8.image.cropAndResize(tensor, box3, [0], [model4.inputs[0].shape[2], model4.inputs[0].shape[1]]);
     const rgb3 = [0.2989, 0.587, 0.114];
     const [red, green, blue] = tf8.split(crop, 3, 3);
     const redNorm = tf8.mul(red, rgb3[0]);
@@ -25331,7 +25333,7 @@ var Human = class {
         return null;
       if (!input)
         return "input is not defined";
-      if (this.tf.ENV.flags.IS_NODE && !(input instanceof this.tf.Tensor)) {
+      if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf18.Tensor)) {
         return "input must be a tensor";
       }
       try {
@@ -25383,7 +25385,7 @@ var Human = class {
     });
     _calculateFaceAngle.set(this, (mesh) => {
       if (!mesh || mesh.length < 300)
-        return {};
+        return {roll: null, yaw: null, pitch: null};
       const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
       const degrees = (theta) => Math.abs(theta * 180 / Math.PI % 360);
       const angle = {

src/blazeface/facemesh.ts

@@ -28,7 +28,6 @@ export class MediaPipeFaceMesh {
       if (mesh && mesh.length > 0) {
         for (const key of Object.keys(coords.MESH_ANNOTATIONS)) annotations[key] = coords.MESH_ANNOTATIONS[key].map((index) => mesh[index]);
       }
-      // const boxRaw = (prediction.box) ? { topLeft: prediction.box.startPoint, bottomRight: prediction.box.endPoint } : null;
       const box = prediction.box ? [
         Math.max(0, prediction.box.startPoint[0]),
         Math.max(0, prediction.box.startPoint[1]),

src/embedding/embedding.ts

@@ -30,12 +30,12 @@ export function enhance(input) {
     // input received from detector is already normalized to 0..1
     // input is also assumed to be straightened
     // const data = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model
-
     // do a tight crop of image and resize it to fit the model
     const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right
     const tensor = input.image || input.tensor;
+    if (!(tensor instanceof tf.Tensor)) return null;
     const crop = (tensor.shape.length === 3)
-      ? tf.image.cropAndResize(tensor.expandDims(0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing
+      ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing
       : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);
 
     // convert to black&white to avoid colorization impact

src/human.ts

@@ -43,7 +43,7 @@ class Human {
   version: string;
   config: typeof config.default;
   state: string;
-  image: { tensor: any, canvas: OffscreenCanvas | HTMLCanvasElement };
+  image: { tensor: typeof tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };
   // classes
   tf: typeof tf;
   draw: typeof draw;
@@ -102,7 +102,7 @@ class Human {
     };
     // export access to image processing
     // @ts-ignore
-    this.image = (input: any) => image.process(input, this.config);
+    this.image = (input: tf.Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);
     // export raw access to underlying models
     this.classes = {
       facemesh,
@@ -132,10 +132,10 @@ class Human {
   }
 
   // quick sanity check on inputs
-  #sanity = (input) => {
+  #sanity = (input): null | string => {
     if (!this.#checkSanity) return null;
     if (!input) return 'input is not defined';
-    if (this.tf.ENV.flags.IS_NODE && !(input instanceof this.tf.Tensor)) {
+    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) {
       return 'input must be a tensor';
     }
     try {
@@ -151,7 +151,7 @@ class Human {
     return 0;
   }
 
-  enhance(input: any): any {
+  enhance(input: typeof tf.Tensor): typeof tf.Tensor | null {
     if (this.config.face.embedding.enabled) return embedding.enhance(input);
     return null;
   }
@@ -267,8 +267,8 @@ class Human {
     }
   }
 
-  #calculateFaceAngle = (mesh) => {
-    if (!mesh || mesh.length < 300) return {};
+  #calculateFaceAngle = (mesh): { roll: number | null, yaw: number | null, pitch: number | null } => {
+    if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };
     const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
     // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
     const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);
@@ -285,7 +285,7 @@ class Human {
     return angle;
   }
 
-  #detectFace = async (input) => {
+  #detectFace = async (input): Promise<any> => {
     // run facemesh, includes blazeface and iris
     // eslint-disable-next-line no-async-promise-executor
     let timeStamp;
@@ -297,10 +297,10 @@ class Human {
       confidence: number,
       boxConfidence: number,
       faceConfidence: number,
-      box: any,
-      mesh:any,
-      meshRaw: any,
-      boxRaw: any,
+      box: [number, number, number, number],
+      mesh: Array<[number, number, number]>
+      meshRaw: Array<[number, number, number]>
+      boxRaw: [number, number, number, number],
       annotations: any,
       age: number,
       gender: string,
@@ -308,7 +308,7 @@ class Human {
       emotion: string,
       embedding: any,
       iris: number,
-      angle: any,
+      angle: { roll: number | null, yaw: number | null, pitch: number | null },
     }> = [];
 
     this.state = 'run:face';
@@ -418,7 +418,45 @@ class Human {
   }
 
   // main detect function
-  async detect(input, userConfig = {}): Promise<{ face: Array<{ any }>, body: Array<{ any }>, hand: Array<{ any }>, gesture: Array<{ any }>, performance: object, canvas: OffscreenCanvas | HTMLCanvasElement } | { error: string }> {
+  async detect(input, userConfig = {}): Promise<{
+      face: Array<{
+        confidence: number,
+        boxConfidence: number,
+        faceConfidence: number,
+        box: [number, number, number, number],
+        mesh: Array<[number, number, number]>
+        meshRaw: Array<[number, number, number]>
+        boxRaw: [number, number, number, number],
+        annotations: any,
+        age: number,
+        gender: string,
+        genderConfidence: number,
+        emotion: string,
+        embedding: any,
+        iris: number,
+        angle: { roll: number | null, yaw: number | null, pitch: number | null },
+      }>,
+      body: Array<{
+        id: number,
+        part: string,
+        position: { x: number, y: number, z: number },
+        score: number,
+        presence: number }>,
+      hand: Array<{
+        confidence: number,
+        box: any,
+        landmarks: any,
+        annotations: any,
+      }>,
+      gesture: Array<{
+        part: string,
+        gesture: string,
+      }>,
+      performance: { any },
+      canvas: OffscreenCanvas | HTMLCanvasElement
+    } | { error: string }> {
+    // end definition
+
     // detection happens inside a promise
     return new Promise(async (resolve) => {
       this.state = 'config';

src/image.ts

@@ -14,7 +14,7 @@ let fx = null;
 // process input image and return tensor
 // input can be tensor, imagedata, htmlimageelement, htmlvideoelement
 // input is resized and run through imagefx filter
-export function process(input, config): { tensor, canvas } {
+export function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {
   let tensor;
   if (input instanceof tf.Tensor) {
     tensor = tf.clone(input);

types/human.d.ts

@@ -14,7 +14,7 @@ declare class Human {
     config: typeof config.default;
     state: string;
     image: {
-        tensor: any;
+        tensor: typeof tf.Tensor;
         canvas: OffscreenCanvas | HTMLCanvasElement;
     };
     tf: typeof tf;
@@ -53,22 +53,54 @@ declare class Human {
         largestKernelOps: any;
     } | {};
     simmilarity(embedding1: Array<number>, embedding2: Array<number>): number;
-    enhance(input: any): any;
+    enhance(input: typeof tf.Tensor): typeof tf.Tensor | null;
     load(userConfig?: null): Promise<void>;
     detect(input: any, userConfig?: {}): Promise<{
         face: Array<{
-            any: any;
+            confidence: number;
+            boxConfidence: number;
+            faceConfidence: number;
+            box: [number, number, number, number];
+            mesh: Array<[number, number, number]>;
+            meshRaw: Array<[number, number, number]>;
+            boxRaw: [number, number, number, number];
+            annotations: any;
+            age: number;
+            gender: string;
+            genderConfidence: number;
+            emotion: string;
+            embedding: any;
+            iris: number;
+            angle: {
+                roll: number | null;
+                yaw: number | null;
+                pitch: number | null;
+            };
         }>;
         body: Array<{
-            any: any;
+            id: number;
+            part: string;
+            position: {
+                x: number;
+                y: number;
+                z: number;
+            };
+            score: number;
+            presence: number;
         }>;
         hand: Array<{
-            any: any;
+            confidence: number;
+            box: any;
+            landmarks: any;
+            annotations: any;
         }>;
         gesture: Array<{
-            any: any;
+            part: string;
+            gesture: string;
         }>;
-        performance: object;
+        performance: {
+            any: any;
+        };
         canvas: OffscreenCanvas | HTMLCanvasElement;
     } | {
         error: string;

types/image.d.ts

@@ -1,4 +1,5 @@
+import * as tf from '../dist/tfjs.esm.js';
 export declare function process(input: any, config: any): {
-    tensor: any;
-    canvas: any;
+    tensor: tf.Tensor;
+    canvas: OffscreenCanvas | HTMLCanvasElement;
 };