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Project Lakechain

Canny Edge

Unstable API

0.8.0

@project-lakechain/canny-edge-detector

 TypeScript

The Canny edge detector makes it possible to extract the edges of images using the Canny edge algorithm. To do so, it takes images as an input, and produces images with the edges extracted as an output. This can be very useful for a variety of machine-learning applications, including image conditioning in image generation.


Original ImageResult Image
Original ImageResult Image


📏 Edge Extraction

Section titled “📏 Edge Extraction”

To use this middleware, you import it in your CDK stack and instantiate it as part of a pipeline.

import { CannyEdgeDetector } from '@project-lakechain/canny-edge-detector';
import { CacheStorage } from '@project-lakechain/core';


class Stack extends cdk.Stack {
  constructor(scope: cdk.Construct, id: string) {
    const cache = new CacheStorage(this, 'Cache');


    // Extracts the edges of images.
    const detector = new CannyEdgeDetector.Builder()
      .withScope(this)
      .withIdentifier('CannyEdgeDetector')
      .withCacheStorage(cache)
      .withSource(source) // 👈 Specify a data source
      .build();
  }
}

Thresholds

Section titled “Thresholds”

You can customize the lower and upper threshold values of the hysterisis procedure used in the Canny edge detection algorithm.

💁 The default values are 100 for the lower threshold and 200 for the upper thresholds.

import { CannyEdgeDetector } from '@project-lakechain/canny-edge-detector';


const detector = new CannyEdgeDetector.Builder()
  .withScope(this)
  .withIdentifier('CannyEdgeDetector')
  .withCacheStorage(cache)
  .withSource(source)
  .withLowerThreshold(150)
  .withUpperThreshold(250)
  .build();

Aperture size

Section titled “Aperture size”

The aperture size represents the size of the Sobel kernel used for edge detection. You can customize it using the withApertureSize API.

💁 The default value is set to 3.

import { CannyEdgeDetector } from '@project-lakechain/canny-edge-detector';


const laplacianProcessor = new CannyEdgeDetector.Builder()
  .withScope(this)
  .withIdentifier('LaplacianProcessor')
  .withCacheStorage(cache)
  .withSource(source)
  .withApertureSize(5)
  .build();

L2 Gradient

Section titled “L2 Gradient”

The L2 gradient is a boolean value that specifies whether to use the equation for finding gradient magnitude. You can customize it using the withL2Gradient API.

💁 The default value is set to false.

import { CannyEdgeDetector } from '@project-lakechain/canny-edge-detector';


const detector = new CannyEdgeDetector.Builder()
  .withScope(this)
  .withIdentifier('CannyEdgeDetector')
  .withCacheStorage(cache)
  .withSource(source)
  .withL2Gradient(true)
  .build();

🏗️ Architecture

Section titled “🏗️ Architecture”

This middleware runs within a Lambda compute, and packages OpenCV to perform the Canny edge detection.

Architecture


🏷️ Properties

Section titled “🏷️ Properties”

Supported Inputs
Section titled “Supported Inputs”
Mime Type Description
image/jpeg JPEG image
image/png PNG image
image/bmp BMP image
image/webp WebP image
Supported Outputs
Section titled “Supported Outputs”
Mime Type Description
image/png PNG image
Supported Compute Types
Section titled “Supported Compute Types”
Type Description
CPU This middleware only supports CPU compute.

📖 Examples

Section titled “📖 Examples”