diff --git a/LineDetection.html b/LineDetection.html index 1610050d6..86cb702c3 100644 --- a/LineDetection.html +++ b/LineDetection.html @@ -25,37 +25,51 @@ this.canvas.height = height; this.ctx = this.canvas.getContext('2d'); this.lastDetectedLine = []; - this.frameCount = 0; - this.allCoordinates = []; + this.isProcessing = false; } async detectLine() { + if (this.isProcessing) return this.canvas.toDataURL(); + this.isProcessing = true; + try { const image = await this.loadImage(`http://${this.raspberryPiIp}:${port.camera}/${endpoint.video}`); this.ctx.drawImage(image, 0, 0, this.width, this.height); const imageData = this.ctx.getImageData(0, 0, this.width, this.height); - const preprocessedImageData = this.preprocessImage(imageData); - const lineCoordinates = this.processImageData(preprocessedImageData); - const filteredCoordinates = this.filterContinuousLine(lineCoordinates); - console.log("coordinates"); - console.log(filteredCoordinates); - if (filteredCoordinates.length > 0) { - this.lastDetectedLine = filteredCoordinates; + + // Convert to grayscale + const data = imageData.data; + for (let i = 0; i < data.length; i += 4) { + const gray = (data[i] + data[i + 1] + data[i + 2]) / 3; + data[i] = gray; + data[i + 1] = gray; + data[i + 2] = gray; } + this.ctx.putImageData(imageData, 0, 0); - if (this.frameCount < 7) { - this.allCoordinates.push(filteredCoordinates); - this.frameCount++; - if (this.frameCount === 7) { - this.writeCoordinatesToFile(this.allCoordinates); - } + // Apply Gaussian blur + const blurredData = this.gaussianBlur(imageData); + this.ctx.putImageData(blurredData, 0, 0); + + // Apply threshold + const thresholdedData = this.threshold(blurredData); + this.ctx.putImageData(thresholdedData, 0, 0); + + // Find contours and get largest + const contours = this.findContours(thresholdedData); + const sortedContours = contours.sort((c1, c2) => c2.length - c1.length); + + if (sortedContours.length > 0) { + this.lastDetectedLine = sortedContours[0]; + this.drawLine(this.lastDetectedLine); } - this.drawLine(this.lastDetectedLine); return this.canvas.toDataURL(); } catch (error) { console.error('Error detecting line:', error); return null; + } finally { + this.isProcessing = false; } } @@ -69,75 +83,104 @@ }); } - preprocessImage(imageData) { + gaussianBlur(imageData) { const data = imageData.data; - const threshold = this.calculateBlackThreshold(data); - - for (let i = 0; i < data.length; i += 4) { - const r = data[i]; - const g = data[i + 1]; - const b = data[i + 2]; - - const brightness = (r + g + b) / 3; - - if (brightness < threshold) { - data[i] = 0; // Set red to min - data[i + 1] = 0; // Set green to min - data[i + 2] = 0; // Set blue to min - } else { - data[i] = 255; // Set red to max - data[i + 1] = 255; // Set green to max - data[i + 2] = 255; // Set blue to max + const result = new ImageData(new Uint8ClampedArray(data), this.width, this.height); + const kernel = [ + [1, 4, 6, 4, 1], + [4, 16, 24, 16, 4], + [6, 24, 36, 24, 6], + [4, 16, 24, 16, 4], + [1, 4, 6, 4, 1] + ]; + const kernelSize = 5; + const kernelSum = 256; + + for (let y = 2; y < this.height - 2; y++) { + for (let x = 2; x < this.width - 2; x++) { + let sum = 0; + for (let ky = 0; ky < kernelSize; ky++) { + for (let kx = 0; kx < kernelSize; kx++) { + const px = x + kx - 2; + const py = y + ky - 2; + const i = (py * this.width + px) * 4; + sum += data[i] * kernel[ky][kx]; + } + } + const i = (y * this.width + x) * 4; + const val = sum / kernelSum; + result.data[i] = val; + result.data[i + 1] = val; + result.data[i + 2] = val; + result.data[i + 3] = 255; } } - - return imageData; + return result; } - calculateBlackThreshold(data) { - let brightnessValues = []; + threshold(imageData) { + const data = imageData.data; + const result = new ImageData(new Uint8ClampedArray(data), this.width, this.height); + for (let i = 0; i < data.length; i += 4) { - const brightness = (data[i] + data[i + 1] + data[i + 2]) / 3; - brightnessValues.push(brightness); + const val = data[i] < 128 ? 0 : 255; + result.data[i] = val; + result.data[i + 1] = val; + result.data[i + 2] = val; + result.data[i + 3] = 255; } - brightnessValues.sort((a, b) => a - b); - return brightnessValues[Math.floor(brightnessValues.length * 0.3)]; // 30th percentile as threshold + return result; } - processImageData(imageData) { - const lineCoordinates = []; - + findContours(imageData) { + const contours = []; + const data = imageData.data; + const visited = new Set(); + for (let y = 0; y < this.height; y++) { for (let x = 0; x < this.width; x++) { - const index = (y * this.width + x) * 4; - const r = imageData.data[index]; + const idx = (y * this.width + x) * 4; + const key = `${x},${y}`; - if (r === 0) { // Check for black pixels (preprocessed black line) - lineCoordinates.push([x, y]); - } + if (data[idx] === 0 && !visited.has(key)) { + const contour = []; + this.traceContour(x, y, data, visited, contour); + if (contour.length > 0) { + contours.push(contour); + } + } } } - return lineCoordinates.sort((a, b) => a[1] - b[1]); + return contours; } - filterContinuousLine(coordinates) { - if (coordinates.length < 2) return coordinates; - - const filteredCoordinates = [coordinates[0]]; - const maxDistance = 20; // Maximum allowed distance between consecutive points - - for (let i = 1; i < coordinates.length; i++) { - const [prevX, prevY] = filteredCoordinates[filteredCoordinates.length - 1]; - const [currentX, currentY] = coordinates[i]; + traceContour(startX, startY, data, visited, contour) { + const stack = [[startX, startY]]; + + while (stack.length > 0) { + const [x, y] = stack.pop(); + const key = `${x},${y}`; + + if (visited.has(key)) continue; - const distance = Math.sqrt(Math.pow(currentX - prevX, 2) + Math.pow(currentY - prevY, 2)); + visited.add(key); + contour.push([x, y]); - if (distance <= maxDistance) { - filteredCoordinates.push(coordinates[i]); + // Check 8-connected neighbors + for (let dy = -1; dy <= 1; dy++) { + for (let dx = -1; dx <= 1; dx++) { + const nx = x + dx; + const ny = y + dy; + + if (nx >= 0 && nx < this.width && ny >= 0 && ny < this.height) { + const idx = (ny * this.width + nx) * 4; + if (data[idx] === 0 && !visited.has(`${nx},${ny}`)) { + stack.push([nx, ny]); + } + } + } } } - - return filteredCoordinates; } drawLine(coordinates) { @@ -153,18 +196,6 @@ }); this.ctx.stroke(); } - - writeCoordinatesToFile(allCoordinates) { - const content = allCoordinates.map((frame, index) => - `Frame ${index + 1}:\n${frame.map(coord => coord.join(',')).join('\n')}\n` - ).join('\n'); - const blob = new Blob([content], { type: 'text/plain' }); - const a = document.createElement('a'); - a.href = URL.createObjectURL(blob); - a.download = 'coordinates.txt'; - a.click(); - URL.revokeObjectURL(a.href); - } } let detector; diff --git a/extensions/src/doodlebot/LineDetection.ts b/extensions/src/doodlebot/LineDetection.ts index 8cbfb845f..7002b29c4 100644 --- a/extensions/src/doodlebot/LineDetection.ts +++ b/extensions/src/doodlebot/LineDetection.ts @@ -1,34 +1,48 @@ -import { createCanvas, loadImage } from 'canvas'; import { endpoint, port } from "./enums"; +import cv from '@u4/opencv4nodejs'; +import axios from 'axios'; export class LineDetector { private lastDetectedLine: number[][] = []; private isProcessing = false; - private canvas: any; - private ctx: any; - constructor(private raspberryPiIp: string, private width = 640, private height = 480) { - this.canvas = createCanvas(this.width, this.height); - this.ctx = this.canvas.getContext('2d'); - } + constructor(private raspberryPiIp: string, private width = 640, private height = 480) {} async detectLine(): Promise { if (this.isProcessing) return this.lastDetectedLine; this.isProcessing = true; try { - const image = await loadImage(`http://${this.raspberryPiIp}:${port.camera}/${endpoint.video}`); - this.ctx.drawImage(image, 0, 0, this.width, this.height); - const imageData = this.ctx.getImageData(0, 0, this.width, this.height); - const preprocessedImageData = this.preprocessImage(imageData); - const lineCoordinates = this.processImageData(preprocessedImageData); - const filteredCoordinates = this.filterContinuousLine(lineCoordinates); + // Get image from endpoint + const response = await axios.get( + `http://${this.raspberryPiIp}:${port.camera}/${endpoint.video}`, + { responseType: 'arraybuffer' } + ); + + // Convert response to cv Mat + const buffer = Buffer.from(response.data); + let mat = cv.imdecode(buffer); + + // Resize if needed + if (mat.cols !== this.width || mat.rows !== this.height) { + mat = mat.resize(this.height, this.width); + } - console.log("coordinates"); - console.log(filteredCoordinates); + // Convert to grayscale and apply threshold + const gray = mat.cvtColor(cv.COLOR_BGR2GRAY); + const blurred = gray.gaussianBlur(new cv.Size(5, 5), 0); + const thresh = blurred.threshold(0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU); - if (filteredCoordinates.length > 0) { - this.lastDetectedLine = filteredCoordinates; + // Find contours + const contours = thresh.findContours(cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE); + + // Get the largest contour (assuming it's the line) + const sortedContours = contours.sort((c1, c2) => c2.area - c1.area); + + if (sortedContours.length > 0) { + // Convert contour points to coordinate array + const coordinates = sortedContours[0].getPoints().map(point => [point.x, point.y]); + this.lastDetectedLine = coordinates; } return this.lastDetectedLine; @@ -39,77 +53,6 @@ export class LineDetector { this.isProcessing = false; } } - - private preprocessImage(imageData: ImageData): ImageData { - const data = imageData.data; - const threshold = this.calculateBlackThreshold(data); - - for (let i = 0; i < data.length; i += 4) { - const r = data[i]; - const g = data[i + 1]; - const b = data[i + 2]; - - const brightness = (r + g + b) / 3; - - if (brightness < threshold) { - data[i] = 0; - data[i + 1] = 0; - data[i + 2] = 0; - } else { - data[i] = 255; - data[i + 1] = 255; - data[i + 2] = 255; - } - } - - return imageData; - } - - private calculateBlackThreshold(data: Uint8ClampedArray): number { - let brightnessValues: number[] = []; - for (let i = 0; i < data.length; i += 4) { - const brightness = (data[i] + data[i + 1] + data[i + 2]) / 3; - brightnessValues.push(brightness); - } - brightnessValues.sort((a, b) => a - b); - return brightnessValues[Math.floor(brightnessValues.length * 0.3)]; - } - - private processImageData(imageData: ImageData): number[][] { - const lineCoordinates: number[][] = []; - - for (let y = 0; y < this.height; y++) { - for (let x = 0; x < this.width; x++) { - const index = (y * this.width + x) * 4; - const r = imageData.data[index]; - - if (r === 0) { - lineCoordinates.push([x, y]); - } - } - } - return lineCoordinates.sort((a, b) => a[1] - b[1]); - } - - private filterContinuousLine(coordinates: number[][]): number[][] { - if (coordinates.length < 2) return coordinates; - - const filteredCoordinates: number[][] = [coordinates[0]]; - const maxDistance = 20; - - for (let i = 1; i < coordinates.length; i++) { - const [prevX, prevY] = filteredCoordinates[filteredCoordinates.length - 1]; - const [currentX, currentY] = coordinates[i]; - - const distance = Math.sqrt(Math.pow(currentX - prevX, 2) + Math.pow(currentY - prevY, 2)); - - if (distance <= maxDistance) { - filteredCoordinates.push(coordinates[i]); - } - } - - return filteredCoordinates; - } } export function createLineDetector(raspberryPiIp: string): () => Promise { diff --git a/package.json b/package.json index 44fd3ca97..bb0721130 100644 --- a/package.json +++ b/package.json @@ -33,5 +33,9 @@ "ts-node": { "typescript": "$typescript" } + }, + "dependencies": { + "@u4/opencv4nodejs": "^7.1.2", + "axios": "^1.7.7" } } \ No newline at end of file diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index 40e737ba1..6a4988cbe 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -7,6 +7,13 @@ settings: importers: .: + dependencies: + '@u4/opencv4nodejs': 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