zsajjad

import UIKit

class ViewController: UIViewController, UIWebViewDelegate {
    
    
    @IBOutlet weak var webView: UIWebView!
    
    override func viewDidLoad() {
        super.viewDidLoad();
        

zsajjad

package fetchsky.androidsample;

import android.annotation.TargetApi;
import android.content.Intent;
import android.net.Uri;
import android.os.Build;
import android.support.v7.app.AppCompatActivity;
import android.os.Bundle;
import android.util.Log;
import android.webkit.WebResourceRequest;

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  /**
   * processImage
   *
   * Responsible for getting image from react native camera and
   * starting image processing.
   *
   * @param {string} uri              Path for the image to be processed
   * @param {object} imageProperties  Other properties of image to be processed
   * @memberof App
   * @author Zain Sajjad

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import ndarray from 'ndarray';
import ops from 'ndarray-ops';
import { Tensor } from 'onnxjs';

export function preProcess(ctx: CanvasRenderingContext2D): Tensor {
  const imageData = ctx.getImageData(0, 0, ctx.canvas.width, ctx.canvas.height);
  const { data, width, height } = imageData;
  const dataTensor = ndarray(new Float32Array(data), [width, height, 4]);
  const dataProcessedTensor = ndarray(new Float32Array(width * height * 3), [1, 3, width, height]);
  ops.assign(dataProcessedTensor.pick(0, 0, null, null), dataTensor.pick(null, null, 2));

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import loadImage from 'blueimp-load-image';

const imageLoaderConfigs = {
  maxWidth: 224,
  maxHeight: 224,
  cover: true,
  crop: true,
  canvas: true,
  crossOrigin: 'Anonymous',
}

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export async function runModel(model: InferenceSession, preProcessedData: Tensor): Promise<[Tensor, number]> {
    const start = new Date();
    try {
        const outputData = await model.run([preProcessedData]);
        const end = new Date();
        const inferenceTime = (end.getTime() - start.getTime());
        const output = outputData.values().next().value;
        return [output, inferenceTime];
    } catch (e) {
        console.error(e);

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import _ from 'lodash';
import { imagenetClasses } from '../data/imagenet';

/**
 * Find top k imagenet classes
 */
export function imagenetClassesTopK(classProbabilities: any, k = 5) {
  const probs = _.isTypedArray(classProbabilities) ? 
      Array.prototype.slice.call(classProbabilities) : classProbabilities;

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import ImagePicker from 'react-native-image-picker';

/* More info on all the options 
 *
 * https://github.com/react-native-community/react-native-image-picker/blob/master/docs/Reference.md#options
 *
 */
const options = {
  title: 'Select Image for styling',
  storageOptions: {

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# Uncomment the next line to define a global platform for your project
platform :ios, '11.0'

target 'MyStylingApp' do
  # Uncomment the next line if you're using Swift or would like to use dynamic frameworks
  # use_frameworks!

  # Linking React Native for Pods Projects
  rn_path = '../node_modules/react-native'
  pod 'yoga', path: "#{rn_path}/ReactCommon/yoga/yoga.podspec"

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import { RNFritzVisionImageStyling } from 'react-native-fritz';

const darkKnights = await RNFritzVisionImageStyling({
  name: 'darkKnights',
  modelIdentifier: '55cdc02f89174e1c8458690d5b8621ae', // Your model identifier here
  customModel: true,
  modelVersion: 1,
});