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https://github.com/Azornes/Comfyui-LayerForge.git
synced 2026-03-25 14:25:44 -03:00
createElement to createCanvas
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@@ -52,10 +52,7 @@ export class CanvasIO {
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const { canvas: maskCanvas, ctx: maskCtx } = createCanvas(this.canvas.width, this.canvas.height);
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const originalShape = this.canvas.outputAreaShape;
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this.canvas.outputAreaShape = null;
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const visibilityCanvas = document.createElement('canvas');
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visibilityCanvas.width = this.canvas.width;
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visibilityCanvas.height = this.canvas.height;
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const visibilityCtx = visibilityCanvas.getContext('2d', { alpha: true });
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const { canvas: visibilityCanvas, ctx: visibilityCtx } = createCanvas(this.canvas.width, this.canvas.height, '2d', { alpha: true });
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if (!visibilityCtx)
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throw new Error("Could not create visibility context");
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if (!maskCtx)
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@@ -94,17 +91,11 @@ export class CanvasIO {
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tempMaskData.data[i + 3] = alpha;
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}
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// Create a temporary canvas to hold the processed mask
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const tempMaskCanvas = document.createElement('canvas');
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tempMaskCanvas.width = this.canvas.width;
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tempMaskCanvas.height = this.canvas.height;
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const tempMaskCtx = tempMaskCanvas.getContext('2d', { willReadFrequently: true });
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const { canvas: tempMaskCanvas, ctx: tempMaskCtx } = createCanvas(this.canvas.width, this.canvas.height, '2d', { willReadFrequently: true });
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if (!tempMaskCtx)
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throw new Error("Could not create temp mask context");
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// Put the processed mask data into a canvas that matches the output area size
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const outputMaskCanvas = document.createElement('canvas');
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outputMaskCanvas.width = toolMaskCanvas.width;
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outputMaskCanvas.height = toolMaskCanvas.height;
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const outputMaskCtx = outputMaskCanvas.getContext('2d', { willReadFrequently: true });
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const { canvas: outputMaskCanvas, ctx: outputMaskCtx } = createCanvas(toolMaskCanvas.width, toolMaskCanvas.height, '2d', { willReadFrequently: true });
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if (!outputMaskCtx)
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throw new Error("Could not create output mask context");
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outputMaskCtx.putImageData(tempMaskData, 0, 0);
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@@ -289,12 +280,9 @@ export class CanvasIO {
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if (!tensor || !tensor.data || !tensor.width || !tensor.height) {
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throw new Error("Invalid tensor data");
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}
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const canvas = document.createElement('canvas');
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const ctx = canvas.getContext('2d', { willReadFrequently: true });
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const { canvas, ctx } = createCanvas(tensor.width, tensor.height, '2d', { willReadFrequently: true });
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if (!ctx)
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throw new Error("Could not create canvas context");
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canvas.width = tensor.width;
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canvas.height = tensor.height;
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const imageData = new ImageData(new Uint8ClampedArray(tensor.data), tensor.width, tensor.height);
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ctx.putImageData(imageData, 0, 0);
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return new Promise((resolve, reject) => {
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@@ -468,10 +456,7 @@ export class CanvasIO {
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}
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async createImageFromData(imageData) {
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return new Promise((resolve, reject) => {
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const canvas = document.createElement('canvas');
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canvas.width = imageData.width;
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canvas.height = imageData.height;
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const ctx = canvas.getContext('2d', { willReadFrequently: true });
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const { canvas, ctx } = createCanvas(imageData.width, imageData.height, '2d', { willReadFrequently: true });
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if (!ctx)
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throw new Error("Could not create canvas context");
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ctx.putImageData(imageData, 0, 0);
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