alphard/Comfyui-LayerForge
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Initial commit

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Project scaffolding and initial file setup.
This commit is contained in:
Dariusz L
2025-07-01 17:02:15 +02:00
parent 038dad759a
commit 562b0db042
15 changed files with 2569 additions and 759 deletions
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81
js/utils/ImageUtils.js
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@@ -1,5 +1,6 @@
import {createModuleLogger} from "./LoggerUtils.js";
import {withErrorHandling, createValidationError} from "../ErrorHandler.js";
const log = createModuleLogger('ImageUtils');
export function validateImageData(data) {
@@ -114,7 +115,7 @@ export function applyMaskToImageData(imageData, maskData) {
};
}
export const prepareImageForCanvas = withErrorHandling(function(inputImage) {
export const prepareImageForCanvas = withErrorHandling(function (inputImage) {
log.info("Preparing image for canvas:", inputImage);
if (Array.isArray(inputImage)) {
@@ -122,7 +123,7 @@ export const prepareImageForCanvas = withErrorHandling(function(inputImage) {
}
if (!inputImage || !inputImage.shape || !inputImage.data) {
throw createValidationError("Invalid input image format", { inputImage });
throw createValidationError("Invalid input image format", {inputImage});
}
const shape = inputImage.shape;
@@ -161,29 +162,29 @@ export const prepareImageForCanvas = withErrorHandling(function(inputImage) {
* @param {HTMLImageElement|HTMLCanvasElement} image - Obraz do konwersji
* @returns {Promise<Object>} Tensor z danymi obrazu
*/
export const imageToTensor = withErrorHandling(async function(image) {
export const imageToTensor = withErrorHandling(async function (image) {
if (!image) {
throw createValidationError("Image is required");
}
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
const ctx = canvas.getContext('2d', { willReadFrequently: true });
canvas.width = image.width || image.naturalWidth;
canvas.height = image.height || image.naturalHeight;
ctx.drawImage(image, 0, 0);
const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
const data = new Float32Array(canvas.width * canvas.height * 3);
for (let i = 0; i < imageData.data.length; i += 4) {
const pixelIndex = i / 4;
data[pixelIndex * 3] = imageData.data[i] / 255;
data[pixelIndex * 3 + 1] = imageData.data[i + 1] / 255;
data[pixelIndex * 3 + 2] = imageData.data[i + 2] / 255;
}
return {
data: data,
shape: [1, canvas.height, canvas.width, 3],
@@ -197,33 +198,33 @@ export const imageToTensor = withErrorHandling(async function(image) {
* @param {Object} tensor - Tensor z danymi obrazu
* @returns {Promise<HTMLImageElement>} Obraz HTML
*/
export const tensorToImage = withErrorHandling(async function(tensor) {
export const tensorToImage = withErrorHandling(async function (tensor) {
if (!tensor || !tensor.data || !tensor.shape) {
throw createValidationError("Invalid tensor format", { tensor });
throw createValidationError("Invalid tensor format", {tensor});
}
const [, height, width, channels] = tensor.shape;
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
const ctx = canvas.getContext('2d', { willReadFrequently: true });
canvas.width = width;
canvas.height = height;
const imageData = ctx.createImageData(width, height);
const data = tensor.data;
for (let i = 0; i < width * height; i++) {
const pixelIndex = i * 4;
const tensorIndex = i * channels;
imageData.data[pixelIndex] = Math.round(data[tensorIndex] * 255);
imageData.data[pixelIndex + 1] = Math.round(data[tensorIndex + 1] * 255);
imageData.data[pixelIndex + 2] = Math.round(data[tensorIndex + 2] * 255);
imageData.data[pixelIndex + 3] = 255;
}
ctx.putImageData(imageData, 0, 0);
return new Promise((resolve, reject) => {
const img = new Image();
img.onload = () => resolve(img);
@@ -239,27 +240,27 @@ export const tensorToImage = withErrorHandling(async function(tensor) {
* @param {number} maxHeight - Maksymalna wysokość
* @returns {Promise<HTMLImageElement>} Przeskalowany obraz
*/
export const resizeImage = withErrorHandling(async function(image, maxWidth, maxHeight) {
export const resizeImage = withErrorHandling(async function (image, maxWidth, maxHeight) {
if (!image) {
throw createValidationError("Image is required");
}
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
const ctx = canvas.getContext('2d', { willReadFrequently: true });
const originalWidth = image.width || image.naturalWidth;
const originalHeight = image.height || image.naturalHeight;
const scale = Math.min(maxWidth / originalWidth, maxHeight / originalHeight);
const newWidth = Math.round(originalWidth * scale);
const newHeight = Math.round(originalHeight * scale);
canvas.width = newWidth;
canvas.height = newHeight;
ctx.imageSmoothingEnabled = true;
ctx.imageSmoothingQuality = 'high';
ctx.drawImage(image, 0, 0, newWidth, newHeight);
return new Promise((resolve, reject) => {
const img = new Image();
img.onload = () => resolve(img);
@@ -274,7 +275,7 @@ export const resizeImage = withErrorHandling(async function(image, maxWidth, max
* @param {number} size - Rozmiar miniatury (kwadrat)
* @returns {Promise<HTMLImageElement>} Miniatura
*/
export const createThumbnail = withErrorHandling(async function(image, size = 128) {
export const createThumbnail = withErrorHandling(async function (image, size = 128) {
return resizeImage(image, size, size);
}, 'createThumbnail');
@@ -285,19 +286,19 @@ export const createThumbnail = withErrorHandling(async function(image, size = 12
* @param {number} quality - Jakość (0-1) dla formatów stratnych
* @returns {string} Base64 string
*/
export const imageToBase64 = withErrorHandling(function(image, format = 'png', quality = 0.9) {
export const imageToBase64 = withErrorHandling(function (image, format = 'png', quality = 0.9) {
if (!image) {
throw createValidationError("Image is required");
}
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
const ctx = canvas.getContext('2d', { willReadFrequently: true });
canvas.width = image.width || image.naturalWidth;
canvas.height = image.height || image.naturalHeight;
ctx.drawImage(image, 0, 0);
const mimeType = `image/${format}`;
return canvas.toDataURL(mimeType, quality);
}, 'imageToBase64');
@@ -307,7 +308,7 @@ export const imageToBase64 = withErrorHandling(function(image, format = 'png', q
* @param {string} base64 - Base64 string
* @returns {Promise<HTMLImageElement>} Obraz
*/
export const base64ToImage = withErrorHandling(function(base64) {
export const base64ToImage = withErrorHandling(function (base64) {
if (!base64) {
throw createValidationError("Base64 string is required");
}
@@ -326,10 +327,10 @@ export const base64ToImage = withErrorHandling(function(base64) {
* @returns {boolean} Czy obraz jest prawidłowy
*/
export function isValidImage(image) {
return image &&
(image instanceof HTMLImageElement || image instanceof HTMLCanvasElement) &&
image.width > 0 &&
image.height > 0;
return image &&
(image instanceof HTMLImageElement || image instanceof HTMLCanvasElement) &&
image.width > 0 &&
image.height > 0;
}
/**
@@ -371,18 +372,18 @@ export function createImageFromSource(source) {
* @param {string} color - Kolor tła (CSS color)
* @returns {Promise<HTMLImageElement>} Pusty obraz
*/
export const createEmptyImage = withErrorHandling(function(width, height, color = 'transparent') {
export const createEmptyImage = withErrorHandling(function (width, height, color = 'transparent') {
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
const ctx = canvas.getContext('2d', { willReadFrequently: true });
canvas.width = width;
canvas.height = height;
if (color !== 'transparent') {
ctx.fillStyle = color;
ctx.fillRect(0, 0, width, height);
}
return new Promise((resolve, reject) => {
const img = new Image();
img.onload = () => resolve(img);