add tests for chessboard corner detection

test/Project.toml

@@ -3,5 +3,7 @@ Artifacts = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
 Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
 LazyArtifacts = "4af54fe1-eca0-43a8-85a7-787d91b784e3"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OpenCV = "f878e3a2-a245-4720-8660-60795d644f2a"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+XML = "72c71f33-b9b6-44de-8c94-c961784809e2"

test/runtests.jl

@@ -3,6 +3,8 @@ using LazyArtifacts
 using OpenCV
 using FileIO
 using Test
+using XML
+using LinearAlgebra
 
 if "OPENCV_TEST_DATA_PATH" in keys(ENV)
     test_dir = joinpath(ENV["OPENCV_TEST_DATA_PATH"], "cv")
@@ -18,4 +20,5 @@ end
     include("test_objdetect.jl")
     include("test_dnn.jl")
     include("test_fileio.jl")
+    include("test_corner_detection.jl")
 end

test/test_corner_detection.jl

@@ -0,0 +1,73 @@
+function _detect_corners(file, n_corners)
+    img = load(file)
+    gry = img[1:1, :, :]
+    cv_n_corners = OpenCV.Size{Int32}(n_corners...)
+    _cv_corners = OpenCV.Mat(Array{Float32}(undef, 2, 1, prod(n_corners)))
+    ret, cv_corners = OpenCV.findChessboardCorners(gry, cv_n_corners, _cv_corners, 0)
+    @assert ret "Failed to detect any corners!"
+    corners = reshape(vec.(eachslice(cv_corners, dims = 3)), n_corners)
+    return corners
+end
+
+function parse_corners_file(file)
+    open(file, "r") do o
+        readuntil(o, "rows:")
+        rows = parse(Int, readuntil(o, "\n"))
+        readuntil(o, "cols:")
+        cols = parse(Int, readuntil(o, "\n"))
+        readuntil(o, "[")
+        corners = [Float32[] for i in 1:cols, j in 1:rows]
+        for i in 1:cols*rows, j in 1:2
+            if i == cols*rows && j == 2
+                break
+            end
+            push!(corners[i], parse(Float32, readuntil(o, ",")))
+        end
+        push!(corners[cols*rows], parse(Float32, readuntil(o, "]")))
+
+        return reverse(permutedims(corners, (2, 1)); dims = 1), (rows, cols)
+    end
+end
+
+function get_list(file)
+    doc = read(file, LazyNode)
+    str = filter(≠('\"'), simple_value(doc[end][end]))
+    list = Dict{String, String}()
+    for line in split(str, '\n')
+        img_file, data_file = split(line)
+        list[img_file] = data_file
+    end
+    return list
+end
+
+function calc_error(ps1, ps2)
+    s = 0.0
+    for (p1, p2) in zip(ps1, ps2)
+        s += LinearAlgebra.norm_sqr(p1 .- p2)
+    end
+    sqrt(s/length(ps1))
+end
+
+function test_one(img_file, data_file)
+    corners, n_corners = parse_corners_file(data_file)
+    detected_corners = _detect_corners(img_file, n_corners)
+    calc_error(corners, detected_corners)
+end
+
+@testset "detecting corners" begin
+
+    path = joinpath(test_dir, "cameracalibration")
+    list = get_list(joinpath(path, "chessboard_list.dat"))
+
+    k, v = first(list)
+    test_one(joinpath(path, k), joinpath(path, v)) # why do we need this?
+
+    @testset "in $k" for (k, v) in list
+
+        img_file = joinpath(path, k)
+        data_file = joinpath(path, v)
+
+        @test test_one(img_file, data_file) < 1
+
+    end
+end