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Merged
ishii-norimi merged 1 commit into from
May 22, 2025
Merged

Updated test logic to directly set input files using buffer data #969

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20 changes: 8 additions & 12 deletions tests/gui/data/upload.test.js
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Original file line number Diff line number Diff line change
@@ -1,11 +1,9 @@
import fs from 'fs'
import path from 'path'

import { getPage } from '../helper/browser'

describe('classification', () => {
/** @type {Awaited<ReturnType<getPage>>} */
let page
let buf
beforeEach(async () => {
page = await getPage()

Expand All @@ -27,24 +25,22 @@ describe('classification', () => {
return canvas.toDataURL()
})
const data = dataURL.replace(/^data:image\/\w+;base64,/, '')
const buf = Buffer.from(data, 'base64')
await fs.promises.writeFile('image_upload.png', buf)
buf = Buffer.from(data, 'base64')
})

afterEach(async () => {
await fs.promises.unlink('image_upload.png')
await page?.close()
})

test('initialize', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
const dataSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_upload.png'))
const uploadFileInput = page.locator('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles({ name: 'image_upload.png', mimeType: 'image/png', buffer: buf })

const svg = await page.waitForSelector('#plot-area svg')
await svg.waitForSelector('.points .datas circle')
expect((await svg.$$('.points .datas circle')).length).toBe(1)
const svg = page.locator('#plot-area svg')
await svg.locator('.points .datas circle').waitFor()
await expect(svg.locator('.points .datas circle').count()).resolves.toBe(1)
})
})
67 changes: 28 additions & 39 deletions tests/gui/view/adaptive_thresholding.test.js
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Original file line number Diff line number Diff line change
@@ -1,6 +1,3 @@
import fs from 'fs'
import path from 'path'

import { getPage } from '../helper/browser'

describe('segmentation', () => {
Expand Down Expand Up @@ -28,55 +25,47 @@ describe('segmentation', () => {
})
const data = dataURL.replace(/^data:image\/\w+;base64,/, '')
const buf = Buffer.from(data, 'base64')
await fs.promises.writeFile('image_adaptive_thresholding.png', buf)

const dataSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')
const uploadFileInput = page.locator('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles({
name: 'image_adaptive_thresholding.png',
mimeType: 'image/png',
buffer: buf,
})

const taskSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = page.locator('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('adaptive_thresholding')
})

afterEach(async () => {
await fs.promises.unlink('image_adaptive_thresholding.png')
await page?.close()
})

test('initialize', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_adaptive_thresholding.png'))
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('adaptive_thresholding')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')

const methods = await buttons.waitForSelector('[name=method]')
await expect((await methods.getProperty('value')).jsonValue()).resolves.toBe('mean')
const k = await buttons.waitForSelector('[name=k]')
await expect((await k.getProperty('value')).jsonValue()).resolves.toBe('3')
const c = await buttons.waitForSelector('[name=c]')
await expect((await c.getProperty('value')).jsonValue()).resolves.toBe('2')
const methods = buttons.locator('[name=method]')
await expect(methods.inputValue()).resolves.toBe('mean')
const k = buttons.locator('[name=k]')
await expect(k.inputValue()).resolves.toBe('3')
const c = buttons.locator('[name=c]')
await expect(c.inputValue()).resolves.toBe('2')
})

test('learn', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_adaptive_thresholding.png'))

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('adaptive_thresholding')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(1)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(1)

const fitButton = await buttons.waitForSelector('input[value=Fit]')
await fitButton.evaluate(el => el.click())
const fitButton = buttons.locator('input[value=Fit]')
await fitButton.dispatchEvent('click')

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(2)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(2)
})
})
45 changes: 22 additions & 23 deletions tests/gui/view/automatic_thresholding.test.js
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Original file line number Diff line number Diff line change
@@ -1,6 +1,3 @@
import fs from 'fs'
import path from 'path'

import { getPage } from '../helper/browser'

describe('segmentation', () => {
Expand Down Expand Up @@ -28,52 +25,54 @@ describe('segmentation', () => {
})
const data = dataURL.replace(/^data:image\/\w+;base64,/, '')
const buf = Buffer.from(data, 'base64')
await fs.promises.writeFile('image_automatic_thresholding.png', buf)

const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
const dataSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_automatic_thresholding.png'))
const uploadFileInput = page.locator('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles({
name: 'image_automatic_thresholding.png',
mimeType: 'image/png',
buffer: buf,
})

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
const taskSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
const modelSelectBox = page.locator('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('automatic_thresholding')
})

afterEach(async () => {
await fs.promises.unlink('image_automatic_thresholding.png')
await page?.close()
})

test('initialize', async () => {
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

const epoch = await buttons.waitForSelector('[name=epoch]')
const epoch = buttons.locator('[name=epoch]')
await expect(epoch.textContent()).resolves.toBe('0')
})

test('learn', async () => {
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(1)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(1)

const epoch = await buttons.waitForSelector('[name=epoch]')
const epoch = buttons.locator('[name=epoch]')
await expect(epoch.textContent()).resolves.toBe('0')
const threshold = await buttons.waitForSelector('span:last-child', { state: 'attached' })
const threshold = buttons.locator('span:last-child', { state: 'attached' })
await expect(threshold.textContent()).resolves.toBe('')

const initButton = await buttons.waitForSelector('input[value=Initialize]')
await initButton.evaluate(el => el.click())
const stepButton = await buttons.waitForSelector('input[value=Step]:enabled')
await stepButton.evaluate(el => el.click())
const initButton = buttons.locator('input[value=Initialize]')
await initButton.dispatchEvent('click')
const stepButton = buttons.locator('input[value=Step]:enabled')
await stepButton.dispatchEvent('click')

await expect(epoch.textContent()).resolves.toBe('1')
await expect(threshold.textContent()).resolves.toMatch(/^[0-9.]+$/)

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(2)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(2)
})
})
66 changes: 28 additions & 38 deletions tests/gui/view/balanced_histogram.test.js
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Original file line number Diff line number Diff line change
@@ -1,6 +1,3 @@
import fs from 'fs'
import path from 'path'

import { getPage } from '../helper/browser'

describe('segmentation', () => {
Expand Down Expand Up @@ -28,54 +25,47 @@ describe('segmentation', () => {
})
const data = dataURL.replace(/^data:image\/\w+;base64,/, '')
const buf = Buffer.from(data, 'base64')
await fs.promises.writeFile('image_balanced_histogram.png', buf)
})

afterEach(async () => {
await fs.promises.unlink('image_balanced_histogram.png')
await page?.close()
})

test('initialize', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
const dataSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_balanced_histogram.png'))
const uploadFileInput = page.locator('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles({
name: 'image_balanced_histogram.png',
mimeType: 'image/png',
buffer: buf,
})

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
const taskSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
const modelSelectBox = page.locator('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('balanced_histogram')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
})

const mincount = await buttons.waitForSelector('input:nth-of-type(1)')
await expect((await mincount.getProperty('value')).jsonValue()).resolves.toBe('100')
afterEach(async () => {
await page?.close()
})

test('learn', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')
test('initialize', async () => {
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_balanced_histogram.png'))
const mincount = buttons.locator('input:nth-of-type(1)')
await expect(mincount.inputValue()).resolves.toBe('100')
})

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('balanced_histogram')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
test('learn', async () => {
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(1)
const threshold = await buttons.waitForSelector('span:last-child', { state: 'attached' })
await expect(threshold.evaluate(el => el.textContent)).resolves.toBe('')
await expect(page.locator('#image-area canvas').count()).resolves.toBe(1)
const threshold = buttons.locator('span:last-child')
await expect(threshold.textContent()).resolves.toBe('')

const fitButton = await buttons.waitForSelector('input[value=Fit]')
await fitButton.evaluate(el => el.click())
const fitButton = buttons.locator('input[value=Fit]')
await fitButton.dispatchEvent('click')

await expect(threshold.evaluate(el => el.textContent)).resolves.toMatch(/^[0-9.]+$/)
await expect(page.$$('#image-area canvas')).resolves.toHaveLength(2)
await expect(threshold.textContent()).resolves.toMatch(/^[0-9.]+$/)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(2)
})
})
62 changes: 24 additions & 38 deletions tests/gui/view/otsu.test.js
View file
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Original file line number Diff line number Diff line change
@@ -1,6 +1,3 @@
import fs from 'fs'
import path from 'path'

import { getPage } from '../helper/browser'

describe('segmentation', () => {
Expand Down Expand Up @@ -28,54 +25,43 @@ describe('segmentation', () => {
})
const data = dataURL.replace(/^data:image\/\w+;base64,/, '')
const buf = Buffer.from(data, 'base64')
await fs.promises.writeFile('image_otsu.png', buf)
})

afterEach(async () => {
await fs.promises.unlink('image_otsu.png')
await page?.close()
})

test('initialize', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
const dataSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_otsu.png'))
const uploadFileInput = page.locator('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles({ name: 'image_otsu.png', mimeType: 'image/png', buffer: buf })

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
const taskSelectBox = page.locator('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
const modelSelectBox = page.locator('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('otsu')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
})

const threshold = await buttons.waitForSelector('span:last-child', { state: 'attached' })
await expect(threshold.evaluate(el => el.textContent)).resolves.toBe('')
afterEach(async () => {
await page?.close()
})

test('learn', async () => {
const dataSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(2) select')
await dataSelectBox.selectOption('upload')
test('initialize', async () => {
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

const uploadFileInput = await page.waitForSelector('#ml_selector #data_menu input[type=file]')
await uploadFileInput.setInputFiles(path.resolve('image_otsu.png'))
const threshold = buttons.locator('span:last-child')
await expect(threshold.textContent()).resolves.toBe('')
})

const taskSelectBox = await page.waitForSelector('#ml_selector dl:first-child dd:nth-child(5) select')
await taskSelectBox.selectOption('SG')
const modelSelectBox = await page.waitForSelector('#ml_selector .model_selection #mlDisp')
await modelSelectBox.selectOption('otsu')
const methodMenu = await page.waitForSelector('#ml_selector #method_menu')
const buttons = await methodMenu.waitForSelector('.buttons')
test('learn', async () => {
const methodMenu = page.locator('#ml_selector #method_menu')
const buttons = methodMenu.locator('.buttons')

await expect(page.$$('#image-area canvas')).resolves.toHaveLength(1)
const threshold = await buttons.waitForSelector('span:last-child', { state: 'attached' })
await expect(threshold.evaluate(el => el.textContent)).resolves.toBe('')
await expect(page.locator('#image-area canvas').count()).resolves.toBe(1)
const threshold = buttons.locator('span:last-child')
await expect(threshold.textContent()).resolves.toBe('')

const fitButton = await buttons.waitForSelector('input[value=Fit]')
await fitButton.evaluate(el => el.click())
const fitButton = buttons.locator('input[value=Fit]')
await fitButton.dispatchEvent('click')

await expect(threshold.evaluate(el => el.textContent)).resolves.toMatch(/^[0-9.]+$/)
await expect(page.$$('#image-area canvas')).resolves.toHaveLength(2)
await expect(threshold.textContent()).resolves.toMatch(/^[0-9.]+$/)
await expect(page.locator('#image-area canvas').count()).resolves.toBe(2)
})
})
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