use env wrapper for browser related code

src/dom/drawLandmarks.ts

-import { getContext2dOrThrow, getDefaultDrawOptions, resolveInput } from 'tfjs-image-recognition-base';
+import { env, getContext2dOrThrow, getDefaultDrawOptions, resolveInput } from 'tfjs-image-recognition-base';
 
 import { FaceLandmarks } from '../classes/FaceLandmarks';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
@@ -11,7 +11,7 @@ export function drawLandmarks(
   options?: DrawLandmarksOptions
 ) {
   const canvas = resolveInput(canvasArg)
-  if (!(canvas instanceof HTMLCanvasElement)) {
+  if (!(canvas instanceof env.getEnv().Canvas)) {
     throw new Error('drawLandmarks - expected canvas to be of type: HTMLCanvasElement')
   }
 

src/dom/extractFaces.ts

@@ -8,6 +8,7 @@ import {
 } from 'tfjs-image-recognition-base';
 
 import { FaceDetection } from '../classes/FaceDetection';
+import { env } from 'tfjs-image-recognition-base';
 
 /**
  * Extracts the image regions containing the detected faces.
@@ -21,9 +22,11 @@ export async function extractFaces(
   detections: Array<FaceDetection | Rect>
 ): Promise<HTMLCanvasElement[]> {
 
+  const { Canvas } = env.getEnv()
+
   let canvas = input as HTMLCanvasElement
 
-  if (!(input instanceof HTMLCanvasElement)) {
+  if (!(input instanceof Canvas)) {
     const netInput = await toNetInput(input)
 
     if (netInput.batchSize > 1) {
@@ -31,7 +34,7 @@ export async function extractFaces(
     }
 
     const tensorOrCanvas = netInput.getInput(0)
-    canvas = tensorOrCanvas instanceof HTMLCanvasElement
+    canvas = tensorOrCanvas instanceof Canvas
       ? tensorOrCanvas
       : await imageTensorToCanvas(tensorOrCanvas)
   }

src/faceLandmarkNet/FaceLandmark68Net.ts

@@ -4,9 +4,9 @@ import { ConvParams, SeparableConvParams } from 'tfjs-tiny-yolov2';
 
 import { depthwiseSeparableConv } from './depthwiseSeparableConv';
 import { extractParams } from './extractParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
 import { FaceLandmark68NetBase } from './FaceLandmark68NetBase';
 import { fullyConnectedLayer } from './fullyConnectedLayer';
-import { loadQuantizedParams } from './loadQuantizedParams';
 import { DenseBlock4Params, NetParams } from './types';
 
 function denseBlock(
@@ -64,10 +64,13 @@ export class FaceLandmark68Net extends FaceLandmark68NetBase<NetParams> {
     })
   }
 
-  protected loadQuantizedParams(uri: string | undefined) {
-    return loadQuantizedParams(uri)
+  protected getDefaultModelName(): string {
+    return 'face_landmark_68_model'
   }
 
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {
+    return extractParamsFromWeigthMap(weightMap)
+  }
 
   protected extractParams(weights: Float32Array) {
     return extractParams(weights)

src/faceLandmarkNet/FaceLandmark68NetBase.ts

@@ -3,7 +3,7 @@ import { IDimensions, isEven, NetInput, NeuralNetwork, Point, TNetInput, toNetIn
 
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
 
-export class FaceLandmark68NetBase<NetParams> extends NeuralNetwork<NetParams> {
+export abstract class FaceLandmark68NetBase<NetParams> extends NeuralNetwork<NetParams> {
 
   // TODO: make super.name protected
   private __name: string
@@ -13,9 +13,7 @@ export class FaceLandmark68NetBase<NetParams> extends NeuralNetwork<NetParams> {
     this.__name = _name
   }
 
-  public runNet(_: NetInput): tf.Tensor2D {
-    throw new Error(`${this.__name} - runNet not implemented`)
-  }
+  public abstract runNet(netInput: NetInput): tf.Tensor2D
 
   public postProcess(output: tf.Tensor2D, inputSize: number, originalDimensions: IDimensions[]): tf.Tensor2D {
 

src/faceLandmarkNet/FaceLandmark68TinyNet.ts

@@ -6,7 +6,7 @@ import { depthwiseSeparableConv } from './depthwiseSeparableConv';
 import { extractParamsTiny } from './extractParamsTiny';
 import { FaceLandmark68NetBase } from './FaceLandmark68NetBase';
 import { fullyConnectedLayer } from './fullyConnectedLayer';
-import { loadQuantizedParamsTiny } from './loadQuantizedParamsTiny';
+import { extractParamsFromWeigthMapTiny } from './extractParamsFromWeigthMapTiny';
 import { DenseBlock3Params, TinyNetParams } from './types';
 
 function denseBlock(
@@ -60,8 +60,12 @@ export class FaceLandmark68TinyNet extends FaceLandmark68NetBase<TinyNetParams>
     })
   }
 
-  protected loadQuantizedParams(uri: string | undefined) {
-    return loadQuantizedParamsTiny(uri)
+  protected getDefaultModelName(): string {
+    return 'face_landmark_68_tiny_model'
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {
+    return extractParamsFromWeigthMapTiny(weightMap)
   }
 
   protected extractParams(weights: Float32Array) {

src/faceLandmarkNet/loadQuantizedParams.ts → src/faceLandmarkNet/extractParamsFromWeigthMap.ts

-import { disposeUnusedWeightTensors, loadWeightMap, ParamMapping } from 'tfjs-image-recognition-base';
+import * as tf from '@tensorflow/tfjs-core';
+import { disposeUnusedWeightTensors, ParamMapping } from 'tfjs-image-recognition-base';
 
 import { loadParamsFactory } from './loadParamsFactory';
 import { NetParams } from './types';
 
-const DEFAULT_MODEL_NAME = 'face_landmark_68_model'
+export function extractParamsFromWeigthMap(
+  weightMap: tf.NamedTensorMap
+): { params: NetParams, paramMappings: ParamMapping[] } {
 
-export async function loadQuantizedParams(
-  uri: string | undefined
-): Promise<{ params: NetParams, paramMappings: ParamMapping[] }> {
-
-  const weightMap = await loadWeightMap(uri, DEFAULT_MODEL_NAME)
   const paramMappings: ParamMapping[] = []
 
   const {

src/faceLandmarkNet/loadQuantizedParamsTiny.ts → src/faceLandmarkNet/extractParamsFromWeigthMapTiny.ts

-import { disposeUnusedWeightTensors, loadWeightMap, ParamMapping } from 'tfjs-image-recognition-base';
+import * as tf from '@tensorflow/tfjs-core';
+import { disposeUnusedWeightTensors, ParamMapping } from 'tfjs-image-recognition-base';
 
 import { loadParamsFactory } from './loadParamsFactory';
 import { TinyNetParams } from './types';
 
-const DEFAULT_MODEL_NAME = 'face_landmark_68_tiny_model'
+export function extractParamsFromWeigthMapTiny(
+  weightMap: tf.NamedTensorMap
+): { params: TinyNetParams, paramMappings: ParamMapping[] } {
 
-export async function loadQuantizedParamsTiny(
-  uri: string | undefined
-): Promise<{ params: TinyNetParams, paramMappings: ParamMapping[] }> {
-
-  const weightMap = await loadWeightMap(uri, DEFAULT_MODEL_NAME)
   const paramMappings: ParamMapping[] = []
 
   const {

src/faceRecognitionNet/FaceRecognitionNet.ts

@@ -3,7 +3,7 @@ import { NetInput, NeuralNetwork, normalize, TNetInput, toNetInput } from 'tfjs-
 
 import { convDown } from './convLayer';
 import { extractParams } from './extractParams';
-import { loadQuantizedParams } from './loadQuantizedParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
 import { residual, residualDown } from './residualLayer';
 import { NetParams } from './types';
 
@@ -78,8 +78,12 @@ export class FaceRecognitionNet extends NeuralNetwork<NetParams> {
       : faceDescriptorsForBatch[0]
   }
 
-  protected loadQuantizedParams(uri: string | undefined) {
-    return loadQuantizedParams(uri)
+  protected getDefaultModelName(): string {
+    return 'face_recognition_model'
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {
+    return extractParamsFromWeigthMap(weightMap)
   }
 
   protected extractParams(weights: Float32Array) {

src/faceRecognitionNet/loadQuantizedParams.ts → src/faceRecognitionNet/extractParamsFromWeigthMap.ts

@@ -9,8 +9,6 @@ import {
 
 import { ConvLayerParams, NetParams, ResidualLayerParams, ScaleLayerParams } from './types';
 
-const DEFAULT_MODEL_NAME = 'face_recognition_model'
-
 function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
 
   const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)
@@ -46,11 +44,10 @@ function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
 
 }
 
-export async function loadQuantizedParams(
-  uri: string | undefined
-): Promise<{ params: NetParams, paramMappings: ParamMapping[] }> {
+export function extractParamsFromWeigthMap(
+  weightMap: tf.NamedTensorMap
+): { params: NetParams, paramMappings: ParamMapping[] } {
 
-  const weightMap = await loadWeightMap(uri, DEFAULT_MODEL_NAME)
   const paramMappings: ParamMapping[] = []
 
   const {

src/mtcnn/Mtcnn.ts

@@ -7,8 +7,8 @@ import { FaceLandmarks5 } from '../classes/FaceLandmarks5';
 import { bgrToRgbTensor } from './bgrToRgbTensor';
 import { CELL_SIZE } from './config';
 import { extractParams } from './extractParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
 import { getSizesForScale } from './getSizesForScale';
-import { loadQuantizedParams } from './loadQuantizedParams';
 import { IMtcnnOptions, MtcnnOptions } from './MtcnnOptions';
 import { pyramidDown } from './pyramidDown';
 import { stage1 } from './stage1';
@@ -146,9 +146,12 @@ export class Mtcnn extends NeuralNetwork<NetParams> {
     )
   }
 
-  // none of the param tensors are quantized yet
-  protected loadQuantizedParams(uri: string | undefined) {
-    return loadQuantizedParams(uri)
+  protected getDefaultModelName(): string {
+    return 'mtcnn_model'
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {
+    return extractParamsFromWeigthMap(weightMap)
   }
 
   protected extractParams(weights: Float32Array) {

src/mtcnn/loadQuantizedParams.ts → src/mtcnn/extractParamsFromWeigthMap.ts

 import * as tf from '@tensorflow/tfjs-core';
-import {
-  disposeUnusedWeightTensors,
-  extractWeightEntryFactory,
-  loadWeightMap,
-  ParamMapping,
-} from 'tfjs-image-recognition-base';
+import { disposeUnusedWeightTensors, extractWeightEntryFactory, ParamMapping } from 'tfjs-image-recognition-base';
 import { ConvParams, FCParams } from 'tfjs-tiny-yolov2';
 
 import { NetParams, ONetParams, PNetParams, RNetParams, SharedParams } from './types';
 
-const DEFAULT_MODEL_NAME = 'mtcnn_model'
-
 function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
 
   const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)
@@ -87,11 +80,10 @@ function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
 
 }
 
-export async function loadQuantizedParams(
-  uri: string | undefined
-): Promise<{ params: NetParams, paramMappings: ParamMapping[] }> {
+export function extractParamsFromWeigthMap(
+  weightMap: tf.NamedTensorMap
+): { params: NetParams, paramMappings: ParamMapping[] } {
 
-  const weightMap = await loadWeightMap(uri, DEFAULT_MODEL_NAME)
   const paramMappings: ParamMapping[] = []
 
   const {

src/ssdMobilenetv1/SsdMobilenetv1.ts

@@ -3,7 +3,7 @@ import { NetInput, NeuralNetwork, Rect, TNetInput, toNetInput } from 'tfjs-image
 
 import { FaceDetection } from '../classes/FaceDetection';
 import { extractParams } from './extractParams';
-import { loadQuantizedParams } from './loadQuantizedParams';
+import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
 import { mobileNetV1 } from './mobileNetV1';
 import { nonMaxSuppression } from './nonMaxSuppression';
 import { outputLayer } from './outputLayer';
@@ -116,8 +116,12 @@ export class SsdMobilenetv1 extends NeuralNetwork<NetParams> {
     return results
   }
 
-  protected loadQuantizedParams(uri: string | undefined) {
-    return loadQuantizedParams(uri)
+  protected getDefaultModelName(): string {
+    return 'ssd_mobilenetv1_model'
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap) {
+    return extractParamsFromWeigthMap(weightMap)
   }
 
   protected extractParams(weights: Float32Array) {

src/ssdMobilenetv1/loadQuantizedParams.ts → src/ssdMobilenetv1/extractParamsFromWeigthMap.ts

@@ -3,15 +3,12 @@ import {
   disposeUnusedWeightTensors,
   extractWeightEntryFactory,
   isTensor3D,
-  loadWeightMap,
   ParamMapping,
 } from 'tfjs-image-recognition-base';
 import { ConvParams } from 'tfjs-tiny-yolov2';
 
 import { BoxPredictionParams, MobileNetV1, NetParams, PointwiseConvParams, PredictionLayerParams } from './types';
 
-const DEFAULT_MODEL_NAME = 'ssd_mobilenetv1_model'
-
 function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
 
   const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings)
@@ -114,11 +111,10 @@ function extractorsFactory(weightMap: any, paramMappings: ParamMapping[]) {
   }
 }
 
-export async function loadQuantizedParams(
-  uri: string | undefined
-): Promise<{ params: NetParams, paramMappings: ParamMapping[] }> {
+export function extractParamsFromWeigthMap(
+  weightMap: tf.NamedTensorMap
+): { params: NetParams, paramMappings: ParamMapping[] } {
 
-  const weightMap = await loadWeightMap(uri, DEFAULT_MODEL_NAME)
   const paramMappings: ParamMapping[] = []
 
   const {

src/tinyFaceDetector/TinyFaceDetector.ts

-import { Point, TNetInput } from 'tfjs-image-recognition-base';
-import { TinyYolov2 as TinyYolov2Base, ITinyYolov2Options } from 'tfjs-tiny-yolov2';
+import * as tf from '@tensorflow/tfjs-core';
+import { ParamMapping, Point, TNetInput } from 'tfjs-image-recognition-base';
+import { ITinyYolov2Options, TinyYolov2 as TinyYolov2Base } from 'tfjs-tiny-yolov2';
+import { TinyYolov2NetParams } from 'tfjs-tiny-yolov2/build/commonjs/tinyYolov2/types';
 
 import { FaceDetection } from '../classes';
-import { BOX_ANCHORS, DEFAULT_MODEL_NAME, IOU_THRESHOLD, MEAN_RGB } from './const';
+import { BOX_ANCHORS, IOU_THRESHOLD, MEAN_RGB } from './const';
 
 export class TinyFaceDetector extends TinyYolov2Base {
 
@@ -29,8 +31,11 @@ export class TinyFaceDetector extends TinyYolov2Base {
     return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))
   }
 
-  protected loadQuantizedParams(modelUri: string | undefined) {
-    const defaultModelName = DEFAULT_MODEL_NAME
-    return super.loadQuantizedParams(modelUri, defaultModelName) as any
+  protected getDefaultModelName(): string {
+    return 'tiny_face_detector_model'
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {
+    return super.extractParamsFromWeigthMap(weightMap)
   }
 }
\ No newline at end of file

src/tinyFaceDetector/const.ts

@@ -10,6 +10,4 @@ export const BOX_ANCHORS = [
   new Point(9.041765, 10.66308)
 ]
 
-export const MEAN_RGB: [number, number, number] = [117.001, 114.697, 97.404]
-
+export const MEAN_RGB: [number, number, number] = [117.001, 114.697, 97.404]
\ No newline at end of file
-export const DEFAULT_MODEL_NAME = 'tiny_face_detector_model'
\ No newline at end of file

src/tinyYolov2/TinyYolov2.ts

-import { Point, TNetInput } from 'tfjs-image-recognition-base';
-import { ITinyYolov2Options, TinyYolov2 as TinyYolov2Base } from 'tfjs-tiny-yolov2';
+import * as tf from '@tensorflow/tfjs-core';
+import { ParamMapping, Point, TNetInput } from 'tfjs-image-recognition-base';
+import { ITinyYolov2Options, TinyYolov2 as TinyYolov2Base, TinyYolov2NetParams } from 'tfjs-tiny-yolov2';
 
 import { FaceDetection } from '../classes';
 import {
@@ -46,8 +47,11 @@ export class TinyYolov2 extends TinyYolov2Base {
     return objectDetections.map(det => new FaceDetection(det.score, det.relativeBox, { width: det.imageWidth, height: det.imageHeight }))
   }
 
-  protected loadQuantizedParams(modelUri: string | undefined) {
-    const defaultModelName = this.withSeparableConvs ? DEFAULT_MODEL_NAME_SEPARABLE_CONV : DEFAULT_MODEL_NAME
-    return super.loadQuantizedParams(modelUri, defaultModelName) as any
+  protected getDefaultModelName(): string {
+    return this.withSeparableConvs ? DEFAULT_MODEL_NAME_SEPARABLE_CONV : DEFAULT_MODEL_NAME
+  }
+
+  protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): { params: TinyYolov2NetParams, paramMappings: ParamMapping[] } {
+    return super.extractParamsFromWeigthMap(weightMap)
   }
 }
\ No newline at end of file