I am trying to learn dlang and decided to develop a regionprops
library in pure d (https://github.com/aferust/regionpropsford). I
borrowed some code and translated into d for performing routines
like connected component labeling and convexhull. The library
does not have any dependency except dlang standard library
phobos. In theory, the library can be used with any image
processing library allowing access to raw image data pointer. I
have recently found out that dcv is dead. So, the library uses
its own data type (Mat2D!T). Although it has been tested with
dlib, you can test it with other libraries such as dcv. I admit
that many code were written clumsily, however my test showed that
it is fast and safe enough so far.
Example usage with dlib:
import std.stdio;
import std.format;
import dlib.image;
import measure.regionprops;
import measure.types;
void main(){
auto img = loadImage("test.png");
auto _imgbin = otsuBinarization(img);
auto imgbin = Mat2D!ubyte(_imgbin.data, _imgbin.height,
_imgbin.width);
// input binary pixels must be 0 for background and 255 for
regions
/*
try RegionProps(imgbin, false) if your OS complains about
max
stack size limit. In this way labeling will be done using
a non-recursive method.
*/
auto rp = new RegionProps(imgbin);
rp.calculateProps();
/+
now you can access blob properties like:
rp.regions[0].orientation
rp.regions[0].majorAxisLength
rp.regions[3].area
+/
auto res = new Image!(PixelFormat.L8)(col_count, row_count);
res.data[] = imgbin.data[];
foreach(i, region; rp.regions){ // mark the centroids
res[region.centroid.x, region.centroid.y] = Color4f(0,
0, 0, 255);
}
saveImage(res, "result.png");
}
I also provide a python binnding based on cython:
usage with opencv:
import numpy as np
import cv2
import rprops
imrgb = cv2.imread('test.png');
img_gray = cv2.cvtColor(imrgb, cv2.COLOR_BGR2GRAY)
binary = img_gray > 200 # do your thresholding somehow
# returns a list containing dicts:
regions = rprops.regionpropsford(binary.astype(np.uint8))
print(regions[0]["Perimeter"])
avalable props (keys of dictionary obj representing a region):
Perimeter
AreaFromContour
Orientation
ConvexHull
Area
Moments
MinorAxis
Solidity
ConvexArea
Eccentricity
ContourPixelList
Centroid
MajorAxis
PixelList
BoundingBox
AspectRatio
EquivalentDiameter
Ellipse
