new demo: Canny operator (rework #177) (#183)

Co-authored-by: Ashwani Rathee <[email protected]>

Author: johnnychen94

Project.toml

@@ -24,6 +24,7 @@ Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
 IndirectArrays = "9b13fd28-a010-5f03-acff-a1bbcff69959"
 MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
 MosaicViews = "e94cdb99-869f-56ef-bcf0-1ae2bcbe0389"
+Noise = "81d43f40-5267-43b7-ae1c-8b967f377efa"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 PaddedViews = "5432bcbf-9aad-5242-b902-cca2824c8663"
 Rotations = "6038ab10-8711-5258-84ad-4b1120ba62dc"
@@ -57,6 +58,7 @@ Images = "0.23"
 IndirectArrays = "0"
 MappedArrays = "0"
 MosaicViews = "0"
+Noise = "0.2"
 OffsetArrays = "1.0"
 PaddedViews = "0"
 Rotations = "1"

docs/examples/contours/canny_edge_demo.jl

@@ -0,0 +1,81 @@
+# ---
+# cover: assets/canny.gif
+# title: Canny Edge Detection
+# author: Ashwani Rathee; Johnny Chen
+# date: 2021-3-20
+# ---
+
+# Canny filter is still a powerful edge detector even though it's invented in 1986 [1].
+# This demo shows you how to use our newly developed package `ImageEdgeDetection` with
+# Canny filter as an example.
+
+using Images, ImageEdgeDetection, Noise
+using ImageEdgeDetection: Percentile
+using TestImages
+
+# !!! info
+#     `ImageEdgeDetection.jl` rewrites many functions which previously exists in `Images.jl` and
+#     will be reexported in `Images` in the future, so you don't need to `using ImageEdgeDetection`
+#     explicitly after that.
+
+# In JuliaImages, any `AbstractArray` can be treated as an image. In this demo, we'll use a generated
+# image for illustration purpose.
+
+# First, we create our test image.
+
+function make_simple_image(sz)
+    img_gray = zeros(Gray{Float64}, sz...)
+    fill_region = map(x->x÷4:3x÷4, sz)
+    img_gray[fill_region...] .= 1
+    img_rot = imrotate(img_gray, pi/4)
+
+    ## Corrupt the image with blur and noise, it makes our canny edge detection 
+    ## function works a little harder since the canny filter is based on the idea
+    ## of finding gradients.
+    img_gauss = imfilter(img_rot, Kernel.gaussian(2))
+
+    ## We use `salt_pepper` filter from `Noise.jl`. Salt-and-pepper noise in general 
+    ## is a noise that modifies a pixel with two different values of noise. 
+    ## Here we only random set pixels to white.
+    img_noise = salt_pepper(img_gauss, 0.05, salt_prob = 0, pepper = 0.9)
+end
+img = make_simple_image((200, 200))
+
+# `ImageEdgeDetection` offers a unified API `detect_edges(img, alg)` with
+# various algorithms. In this demo we'll show how to use the `Canny`
+# operator [1]. First we'll need to create an algorithm instance of `Canny`.
+
+alg = Canny(spatial_scale=1, high=Percentile(80), low=Percentile(20))
+
+# and then apply this instance as parameters to `detect_edges`, with the Julia
+# [multiple dispatch mechanism](https://docs.julialang.org/en/v1/manual/methods/#Methods),
+# `detect_edges` knows which algorithm implementation should be called with
+# the `alg` information.
+
+edges = detect_edges(img, alg)
+mosaicview(img, edges; nrow=1)
+
+# Now let's see how different Canny parameters changes the result, and also see
+# how it works on real world images:
+
+cameraman = testimage("cameraman")
+canny(σ) = Canny(spatial_scale=σ, high=Percentile(80), low=Percentile(20))
+simple_results = map(σ->detect_edges(img, canny(σ)), 1:5)
+cameraman_results = map(σ->detect_edges(cameraman, canny(σ)), 1:5)
+
+mosaicview(
+    mosaicview(img, cameraman),
+    map(mosaicview, simple_results, cameraman_results)...;
+    nrow=1
+)
+
+# As you can see, higher `spatial_scale` tells the Canny operator to ignore small
+# details and thus gives a "clean" edge result; whether it is a correct/useful edge
+# result depends on how you interpret it.
+
+save("assets/canny.gif", cat(cameraman, cameraman_results...; dims=3); fps=2) #src
+
+# # References
+
+# [1] J. Canny, "A Computational Approach to Edge Detection," in _IEEE Transactions on Pattern Analysis and Machine Intelligence_, vol.
+# PAMI-8, no. 6, pp. 679-698, Nov. 1986, doi: 10.1109/TPAMI.1986.4767851.