Remove pyplot strong dependency

.github/workflows/ci.yml

@@ -10,7 +10,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.4'  # Min Julia version supported
+          - '1.9'  # Min Julia version supported
           - '1'    # Expands to latest version
         os:
           - ubuntu-latest

Project.toml

@@ -1,7 +1,7 @@
 name = "ImageProjectiveGeometry"
 uuid = "b9d14576-938f-5430-9d4c-b7d7de1409d6"
 author = ["Peter Kovesi <peter.kovesi@gmail.com>"]
-version = "0.3.6"
+version = "0.4.0"
 
 [deps]
 DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2"
@@ -11,16 +11,22 @@ Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
+[weakdeps]
+PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
+
+[extensions]
+ImageProjectiveGeometryPyPlotExt = "PyPlot"
+
 [compat]
 DSP = "0.5 - 0.7"
 FileIO = "1"
 ImageFiltering = "0.4 - 0.7"
 Images = "0.20 - 0.25"
 Interpolations = "0.10 - 0.14"
 PyPlot = "2.5 - 2.11"
-julia = "1.4"
+julia = "1.9"

README.md

@@ -23,6 +23,13 @@ pkg> add ImageProjectiveGeometry
 help?> ImageProjectiveGeometry  # Lists a summary of the package functions 
 ```
 
+On Julia versions >=1.9, the `PyPlot` package is not added automatically anymore, but used as a weak dependency. To get the plotting functionality back, import `PyPlot` together with `ImageProjectiveGeometry` like this:
+
+```Julia
+using PyPlot
+using ImageProjectiveGeometry
+```
+
 ## Summary
 
 This Image Projective Geometry package is intended as a starting point for the development of a library of projective geometry functions for computer vision in Julia.

ext/ImageProjectiveGeometryPyPlotExt.jl

@@ -0,0 +1,196 @@
+module ImageProjectiveGeometryPyPlotExt
+using LinearAlgebra
+using Random
+using PyPlot
+using ImageProjectiveGeometry
+
+include("ransacdemo.jl")
+
+function plot_briefcoords(S, nPairs, rc)
+    figure(200); clf
+        R = (S.-1)/2 .+ 1
+        axis([-R, R, -R, R])
+
+        for n = 1:nPairs
+            plot(rc[2, 2*n-1:2*n], rc[1, 2*n-1:2*n], color = rand(3), 
+                 linewidth = 3)
+        end
+
+        axis("equal")
+
+        # Determine distances between pairs and display histogram
+        sdist = zeros(nPairs)
+        for n = 1:nPairs
+            sdist[n] = norm(rc[:,2*n-1] - rc[:,2*n])
+        end
+
+        (e, counts) = hist(sdist, 0:.5:S)
+        e = e .+ 0.5
+        figure(30); clf()
+        PyPlot.bar(x=e, height = counts[2:end], width=e[2]-e[1])
+        title("Histogram of distances between pairs")
+end
+
+function plot_nonmaxsuppts(fig, img, c, r, cols, rows)
+    # If an image has been supplied display it and overlay corners.
+    if !isempty(img)
+        print("Plotting corners")
+        PyPlot.figure(fig)
+        PyPlot.clf()
+        PyPlot.imshow(img)
+        PyPlot.set_cmap(PyPlot.ColorMap("gray"))
+        PyPlot.plot(c,r,"r+")
+        PyPlot.axis([1,cols,rows,1])
+        PyPlot.title("Corners detected")
+    end
+end
+
+
+"""
+hline - Plot a 2D line defined in homogeneous coordinates.
+
+Function for ploting 2D homogeneous lines defined by 2 points
+or a line defined by a single homogeneous vector
+```
+Usage 1:   hline(p1,p2, linestyle="b-")
+Arguments: p1, p2 -  Two 3-vectors defining points in homogeneous
+                     coordinates
+
+Usage 2:    hline(l, linestyle="b-")
+Argument:   l - A 3-vector defining a line in homogeneous coordinates
+
+```
+Note that in the case where a homogeneous line is supplied as the
+argument the extent of the line drawn depends on the current axis
+limits.  This will require you to set the desired limits with a call
+to PyPlot.axis() prior to calling this function.
+
+"""
+function hline(p1i::Vector, p2i::Vector, linestyle::String="b-")
+    # Case when 2 homogeneous points are supplied
+
+    p1 = p1i./p1i[3]    # make sure homogeneous points lie in z=1 plane
+    p2 = p2i./p2i[3]
+
+#    hold(true)
+    plot([p1[1], p2[1]], [p1[2], p2[2]], linestyle);
+end
+
+# Case when homogeneous line is supplied
+function hline(li::Vector, linestyle::String="b-")
+
+    l = li./li[3]   # ensure line in z = 1 plane (not needed?)
+
+    if abs(l[1]) > abs(l[2])   # line is more vertical
+        p1 = hcross(l, [0, -1, PyPlot.ylim()[1]])
+        p2 = hcross(l, [0, -1, PyPlot.ylim()[2]])
+
+    else                       # line more horizontal
+        p1 = hcross(l, [-1, 0, PyPlot.xlim()[1]])
+        p2 = hcross(l, [-1, 0, PyPlot.xlim()[2]])
+    end
+
+#    hold(true)
+    plot([p1[1], p2[1]], [p1[2], p2[2]], linestyle);
+end
+
+
+"""
+plotcamera - Plots graphical representation of camera(s) showing pose.
+
+```
+Usage: plotcamera(C, l; col=[0,0,1], plotCamPath=false, fig=nothing)
+
+Arguments:
+           C - Camera structure (or array of Camera structures)
+           l - The length of the sides of the rectangular cone indicating
+               the camera's field of view.
+Keyword Arguments:
+         col - Optional three element vector specifying the RGB colour to
+               use. Defaults to blue.
+ plotCamPath - Optional flag true/false to plot line joining camera centre
+               positions. If omitted or empty defaults to false.
+         fig - Optional figure number to be used. If not specified a new
+               figure is created.
+```
+
+The function plots into the current figure a graphical representation of one
+or more cameras showing their pose.  This consists of a rectangular cone,
+with its vertex at the camera centre, indicating the camera's field of view.
+The camera's coordinate X and Y axes are also plotted at the camera centre.
+
+See also: Camera
+"""
+function plotcamera(Ci, l, col=[0,0,1], plotCamPath=false, fig=nothing)
+
+    if isa(Ci, Array)
+        C = Ci
+    else
+        C = [Ci]
+    end
+
+    figure(fig)
+    for i = 1:eachindex(C)
+
+        if C[i].rows == 0 || C[i].cols == 0
+            @warn("Camera rows and cols not specified")
+            continue
+        end
+
+        f = C[i].fx  # Use fx as the focal length
+
+        if i > 1 && plotCamPath
+            plot3D([C[i-1].P[1], C[i].P[1]],
+                   [C[i-1].P(2), C[i].P[2]],
+                   [C[i-1].P(3), C[i].P[3]])
+        end
+
+        # Construct transform from camera coordinates to world coords
+        Tw_c = [C[i].Rc_w'  C[i].P
+                 0 0 0        1  ]
+
+        # Generate the 4 viewing rays that emanate from the principal point and
+        # pass through the corners of the image.
+        ray = zeros(3,4)
+        ray[:,1] = [-C[i].cols/2, -C[i].rows/2, f]
+        ray[:,2] = [ C[i].cols/2, -C[i].rows/2, f]
+        ray[:,3] = [ C[i].cols/2,  C[i].rows/2, f]
+        ray[:,4] = [-C[i].cols/2,  C[i].rows/2, f]
+
+        # Scale rays to distance l from the focal plane and make homogeneous
+        ray = makehomogeneous(ray*l/f)
+        ray = Tw_c*ray                 # Transform to world coords
+
+        for n = 1:4             # Draw the rays
+            plot3D([C[i].P[1], ray[1,n]],
+                   [C[i].P[2], ray[2,n]],
+                   [C[i].P[3], ray[3,n]],
+                   color=col)
+        end
+
+        # Draw rectangle joining ends of rays
+        plot3D([ray[1,1], ray[1,2], ray[1,3], ray[1,4], ray[1,1]],
+               [ray[2,1], ray[2,2], ray[2,3], ray[2,4], ray[2,1]],
+               [ray[3,1], ray[3,2], ray[3,3], ray[3,4], ray[3,1]],
+               color=col)
+
+        # Draw and label axes
+        X = Tw_c[1:3,1]*l .+ C[i].P
+        Y = Tw_c[1:3,2]*l .+ C[i].P
+        Z = Tw_c[1:3,3]*l .+ C[i].P
+
+        plot3D([C[i].P[1], X[1,1]], [C[i].P[2], X[2,1]], [C[i].P[3], X[3,1]],
+               color=col)
+        plot3D([C[i].P[1], Y[1,1]], [C[i].P[2], Y[2,1]], [C[i].P[3], Y[3,1]],
+               color=col)
+        #    plot3D([C[i].P[1], Z(1,1)], [C[i].P[2], Z(2,1)], [C[i].P[3], Z(3,1)],...
+        #           color=col)
+        text3D(X[1], X[2], X[3], "X", color=col)
+        text3D(Y[1], Y[2], Y[3], "Y", color=col)
+
+    end
+
+end
+
+end # module
+

src/ransacdemo.jl → ext/ransacdemo.jl

@@ -20,12 +20,6 @@ PK March     2016
 
 ---------------------------------------------------------------------=#
 
-export fitlinedemo, fitplanedemo
-export fitfunddemo, fithomogdemo
-
-using ImageProjectiveGeometry, PyPlot, Printf, FileIO
-
-#-----------------------------------------------------------------------
 """
 fitlinedemo - Demonstrates RANSAC line fitting.
 
@@ -96,7 +90,7 @@ function fitlinedemo(outliers, sigma, t::Real, feedback::Bool = false)
     (V, P, inliers) = ransacfitline(XYZ, t, feedback)
 
     if feedback
-        @printf("Number of Inliers: %d\n", length(inliers))
+	println("Number of Inliers: $(length(inliers))")
     end
 
     # Plot the inlier points blue, with the outlier points in red.
@@ -189,10 +183,10 @@ function fitplanedemo(outliers, sigma, t, feedback::Bool = false)
     (Bfitted, P, inliers) = ransacfitplane(XYZ, t, feedback)
 
     Bfitted = Bfitted/Bfitted[4]
-    @printf("Original plane coefficients:  ")
-    @printf("%8.3f %8.3f %8.3f %8.3f \n",B[1], B[2], B[3], B[4])
-    @printf("Fitted plane coefficients:    ")
-    @printf("%8.3f %8.3f %8.3f %8.3f \n",Bfitted[1], Bfitted[2], Bfitted[3], Bfitted[4])
+    print("Original plane coefficients:  ")
+    print("%8.3f %8.3f %8.3f %8.3f \n",B[1], B[2], B[3], B[4])
+    print("Fitted plane coefficients:    ")
+    print("%8.3f %8.3f %8.3f %8.3f \n",Bfitted[1], Bfitted[2], Bfitted[3], Bfitted[4])
 
     # Display the triangular patch formed by the 3 points that gave the
     # plane of maximum consensus
@@ -201,8 +195,8 @@ function fitplanedemo(outliers, sigma, t, feedback::Bool = false)
     plot3D(pts[:,1], pts[:,2], pts[:,3], "k-")
 #    hold(false)
 
-    @printf("\nRotate image so that the triangular patch is seen edge on\n")
-    @printf("These are the points that form the plane of max consensus.\n\n")
+    print("\nRotate image so that the triangular patch is seen edge on\n")
+    print("These are the points that form the plane of max consensus.\n\n")
 
 end
 
@@ -246,7 +240,7 @@ function fitfunddemo(img1=[], img2=[])
     figure(2); axis("off"); 
     keypause()
 
-    @printf("Matching features...\n")
+    print("Matching features...\n")
     (m1,m2) = matchbycorrelation(copy(img1), [r1';c1'], copy(img2), [r2';c2'], w, dmax)
 
     # Display putative matches
@@ -271,9 +265,9 @@ function fitfunddemo(img1=[], img2=[])
     (F, inliers) = ransacfitfundmatrix(x1, x2, t, true)
 #   (F, inliers) = ransacfitaffinefundmatrix(x1, x2, t, true)    
 
-    @printf("Number of inliers was %d (%d%%) \n", 
+    print("Number of inliers was %d (%d%%) \n", 
 	    length(inliers),round(Int, 100*length(inliers)/nMatch))
-    @printf("Number of putative matches was %d \n", nMatch)
+    print("Number of putative matches was %d \n", nMatch)
 
     # Display both images overlayed with inlying matched feature points
     figure(4); clf();  imshow(img1);  axis("off") # hold(true)
@@ -285,7 +279,7 @@ function fitfunddemo(img1=[], img2=[])
     title("Inlying matches")
 #    hold(false)
 
-    @printf("Step through each epipolar line [y/n]?\n")
+    print("Step through each epipolar line [y/n]?\n")
     response = readline()
     if response[1] == 'n'
 	return
@@ -320,7 +314,7 @@ function fitfunddemo(img1=[], img2=[])
 	keypause()
     end
 
-    @printf("                                         \n")
+    print("                                         \n")
 
 end    
 
@@ -357,7 +351,7 @@ function fithomogdemo(img1=[], img2=[])
     (cim1, r1, c1) = shi_tomasi(img1, 1, radius=nonmaxrad, N=100, img=img1, fig=1)
     (cim2, r2, c2) = shi_tomasi(img2, 1, radius=nonmaxrad, N=100, img=img2, fig=2)
     keypause()
-    @printf("Matching features...\n")
+    print("Matching features...\n")
     (m1,m2) = matchbycorrelation(img1, [r1';c1'], img2, [r2';c2'], w, dmax)
 
     # Display putative matches
@@ -377,9 +371,9 @@ function fithomogdemo(img1=[], img2=[])
     t = .001  # Distance threshold for deciding outliers
     (H, inliers) = ransacfithomography(x1, x2, t)
 
-    @printf("Number of inliers was %d (%d%%) \n", 
+    print("Number of inliers was %d (%d%%) \n", 
 	    length(inliers),round(Int, 100*length(inliers)/nMatch))
-    @printf("Number of putative matches was %d \n", nMatch) 
+    print("Number of putative matches was %d \n", nMatch) 
 
     # Display both images overlayed with inlying matched feature points
     figure(4); clf();  imshow(img1);  # hold(true)
@@ -390,6 +384,5 @@ function fithomogdemo(img1=[], img2=[])
     end
 
     title("Inlying matches")
-#    hold(false)
 end