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| Original file line number | Diff line number | Diff line change |
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| @@ -1,4 +1,3 @@ | ||
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| let spec_files = ['**/*.test.ts'].concat( | ||
| process.env.EXCLUDE_UNCOMPRESSED | ||
| ? ['!**/*.uncompressed.test.ts'] | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| import { NeuralNetwork } from 'tfjs-image-recognition-base'; | ||
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| export type TestEnv = { | ||
| loadImage: (uri: string) => Promise<HTMLImageElement> | ||
| loadJson: <T> (uri: string) => Promise<T> | ||
| initNet: <TNet extends NeuralNetwork<any>>( | ||
| net: TNet, | ||
| uncompressedFilename?: string | boolean, | ||
| isUnusedModel?: boolean | ||
| ) => any | ||
| } |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,32 @@ | ||
| import * as fs from 'fs'; | ||
| import * as path from 'path'; | ||
| import { NeuralNetwork } from 'tfjs-image-recognition-base'; | ||
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| import { env } from '../src'; | ||
| import { TestEnv } from './Environment'; | ||
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| require('@tensorflow/tfjs-node') | ||
| const canvas = require('canvas') | ||
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| const { Canvas, Image, ImageData } = canvas | ||
| env.monkeyPatch({ Canvas, Image, ImageData }) | ||
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| async function loadImageNode(uri: string): Promise<HTMLImageElement> { | ||
| return canvas.loadImage(path.resolve(__dirname, '../', uri)) | ||
| } | ||
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| async function loadJsonNode<T>(uri: string): Promise<T> { | ||
| return JSON.parse(fs.readFileSync(path.resolve(__dirname, '../', uri)).toString()) | ||
| } | ||
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| export async function initNetNode<TNet extends NeuralNetwork<any>>(net: TNet) { | ||
| await net.loadFromDisk(path.resolve(__dirname, '../weights')) | ||
| } | ||
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| const nodeTestEnv: TestEnv = { | ||
| loadImage: loadImageNode, | ||
| loadJson: loadJsonNode, | ||
| initNet: initNetNode | ||
| } | ||
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| global['nodeTestEnv'] = nodeTestEnv |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,52 +1,41 @@ | ||
| import * as tf from '@tensorflow/tfjs-core'; | ||
| import { fetchNetWeights, NeuralNetwork } from 'tfjs-image-recognition-base'; | ||
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| import { env, fetchImage, fetchJson } from '../src'; | ||
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| export let fs: any, path: any, canvas: any | ||
| import { fetchImage, fetchJson } from '../src'; | ||
| import { TestEnv } from './Environment'; | ||
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| jasmine.DEFAULT_TIMEOUT_INTERVAL = 60000 | ||
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| if (env.isNodejs()) { | ||
| require('@tensorflow/tfjs-node') | ||
| fs = require('fs') | ||
| path = require('path') | ||
| canvas = require('canvas') | ||
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| const { Canvas, Image, ImageData } = canvas | ||
| env.monkeyPatch({ Canvas, Image, ImageData }) | ||
| } else { | ||
| if ((window['__karma__'].config.jasmine.args as string[]).some(arg => arg === 'backend_cpu')) { | ||
| tf.setBackend('cpu') | ||
| } | ||
| if (typeof window !== 'undefined' && window['__karma__'] && (window['__karma__'].config.jasmine.args as string[]).some(arg => arg === 'backend_cpu')) { | ||
| tf.setBackend('cpu') | ||
| } | ||
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| export async function initNet<TNet extends NeuralNetwork<any>>( | ||
| async function loadImageBrowser(uri: string): Promise<HTMLImageElement> { | ||
| return fetchImage(`base${uri.startsWith('/') ? '' : '/'}${uri}`) | ||
| } | ||
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| async function loadJsonBrowser<T>(uri: string): Promise<T> { | ||
| return fetchJson<T>(`base${uri.startsWith('/') ? '' : '/'}${uri}`) | ||
| } | ||
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| async function initNetBrowser<TNet extends NeuralNetwork<any>>( | ||
| net: TNet, | ||
| uncompressedFilename: string | boolean, | ||
| isUnusedModel: boolean = false | ||
| ) { | ||
| if (env.isNodejs()) { | ||
| await net.loadFromDisk(path.resolve(__dirname, '../weights')) | ||
| } else { | ||
| const url = uncompressedFilename | ||
| ? await fetchNetWeights(`base/weights_uncompressed/${uncompressedFilename}`) | ||
| : (isUnusedModel ? 'base/weights_unused' : 'base/weights') | ||
| await net.load(url) | ||
| } | ||
| const url = uncompressedFilename | ||
| ? await fetchNetWeights(`base/weights_uncompressed/${uncompressedFilename}`) | ||
| : (isUnusedModel ? 'base/weights_unused' : 'base/weights') | ||
| await net.load(url) | ||
| } | ||
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| export async function loadImage(uri: string): Promise<HTMLImageElement> { | ||
| if (env.isNodejs()) { | ||
| return canvas.loadImage(path.resolve(__dirname, '../', uri)) | ||
| } | ||
| return fetchImage(`base${uri.startsWith('/') ? '' : '/'}${uri}`) | ||
| const browserTestEnv: TestEnv = { | ||
| loadImage: loadImageBrowser, | ||
| loadJson: loadJsonBrowser, | ||
| initNet: initNetBrowser | ||
| } | ||
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| export async function loadJson<T>(uri: string): Promise<T> { | ||
| if (env.isNodejs()) { | ||
| return JSON.parse(fs.readFileSync(path.resolve(__dirname, '../', uri)).toString()) | ||
| } | ||
| return fetchJson<T>(`base${uri.startsWith('/') ? '' : '/'}${uri}`) | ||
| export function getTestEnv(): TestEnv { | ||
| return global['nodeTestEnv'] || browserTestEnv | ||
| } | ||
|
|
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