I want to apply Unsupervised learning on images through OpenCV and python to detect and categorise some special patterns in image and form different clutters.
If this image is example how I can detect the yellow pattern?
Very interesting problem. If circle detection is showing good matches, you can consider the difference of color histograms in patches inside and outside the circles. Also worth investigating is the difference in edge histograms in small windows on the image.
To check the inside of the circles, you can take a square that is about 1.4 times wide as the circle radius, with the same center as the circle's center. For the outside, take a few squares about this size but are located further than the radius in x and y directions. I think approximate values like these should do.
Related
Problem
I'm trying to use opencv2 to detect PlayStation Move Motion Controllers in still images. In an attempt to increase the contrast between the orbs and the backgrounds, I decided to modify the input image to automatically scale the brightness level between the image's mean level and 96 above for each channel, then when converting to grayscale, taking the maximum value instead of the default transform, since some orbs are saturated but not "bright".
However, my best attempts at adjusting the parameters seems to not work well, detecting circles that aren't there over the obvious ones.
What can I do to improve the accuracy of the detection? What other improvements or algorithms do you think I could use?
Samples
In order of best to worst:
2 Wands, 1 Wand detected (showing all 2 detected circles)
2 Wands, 1 Wand detected with many nonexistent circles (showing top 4 circles)
1 Wand (against a dark background), 6 total circles, the lowest-ranked of which is the correct one (showing all 6 circles)
1 Wand (against a dark background), 44 total circles detected, none of which are that Wand (showing all 44 circles)
I am using this function call:
cv2.HoughCircles(img_gray,cv2.HOUGH_GRADIENT,
dp=1, minDist=24, param1=90, param2=25,
minRadius=2, maxRadius=48)
All images are resized and cropped to 640x480 (the resolution of the PS3 Eye). No blur is performed.
I think hough circles is the wrong approach for you, as you are not really looking for circles. You are looking for circular areas with strong intensity. Use e.g. blob detection instead, I linked a guide:
https://www.learnopencv.com/blob-detection-using-opencv-python-c/
In the blob detection, you need to set the parameters to get a proper high-intensity circular area.
as the other user said, hough circles arent the best approach here because hough circles look for perfect circles only. whereas your target is "circular" but not a circle (due to motion blur, light bleed/reflection, noise etc)
I suggest converting the image to HSV then filtering by hue/color and intensities to get a binary threshold instead of using grayscale directly (that will help remove background & noise and limit the search area)
then using findContours() (faster than blob detection), check for contours of high circularity and expected size/area range and maybe even solidity.
area = cv2.contourArea(contour)
perimeter = cv2.arcLength(contour,True)
circularity = 4*np.pi*area / (perimeter**2)
solidity = area/cv2.contourArea(cv2.convexHull(contour))
your biggest problem will be the orb contour merging with the background due to low contrast. so maybe some adaptive threshold could help
I created my own little 2D-Engine with DirectX (okey, should be more like a GUI in the end) and tried to create rounded edges for a simple Rectangle. Since I never done this with a graphics framework before I had no idea how to supply this.
For now, I just overlapped 5 Rectangles and 4 circles (the circles are used for the rounded edges). It does work with opaque colors but if I add alpha into the rectangles the circles are making problems. (Shown in the image below - i should have choose another colors...)
<# Open Image #>
I can't find a solution myself (I googled and whondered I found nothing about rounded edges in DirectX) and I do believe there is a much powerful and faster method doing this. So my final question is, what are the common algorythm to create a rectangle with rounded edges in Direct3D9 ?
The common way to draw rounded quads is the use of textures with an alphachannel. It's very easy and the most of the gui's uses images to achieve a specific look. If you draw only single-colored boxes it may look very generic after a while (even if they have fancy rounded corners ;) ).
But if you want to draw rounded quads directly, I would suppose to generate a custom geometry, which fits the desired area directly without overlapping (need for alphablending). In you case it would be something like this:
The more triangles you're using for the corner the smoother it will look.
I am currently working on a program to detect coordinates of pool balls in an image of a pool table taken from an arbitrary point.
I first calculated the table corners and warped the perspective of the image to obtain a bird's eye view. Unfortunately, this made the spherical balls appear to be slightly elliptical as shown below.
In an attempt to detect the ellipses, I extracted all but the green felt area and used a Hough transform algorithm (HoughCircles) on the resulting image shown below. Unfortunately, none of the ellipses were detected (I can only assume because they are not circles).
Is there any better method of detecting the balls in this image? I am technically using JavaCV, but OpenCV solutions should be suitable. Thank you so much for reading.
The extracted BW image is good but it needs some morphological filters to eliminate noises then you can extract external contours of each object (by cvFindContours) and fit best ellipse to them (by cvFitEllipse2).
I would like to identify the center of an SVG, so that I can manipulate multiple SVGs with ease.
I am trying to make multiple examples of the basic polygons (3 to 8 sides), and quickly realized that I either hade to make my own, which involves a lot of math, or I could pull from wikipedia the current ones. The problem with the former is that it takes a lot of time to translate the coordinates from Sketchup. The problem with the latter is that they are oriented differently and of different size.
I know that you can transform, scale, and rotate the SVG, but I need to know the coordinates of the center of the SVG. How do I find this out, so I can set universal manipulations?
Take the transform="rotate(degrees x y)", I need to know the center to accomplish this.
JS Fiddle
Here, I would like to set all the centers to the same, and then scale them to the same height and width, and potentially rotate them individually so that they all have a flat bottom, not a vertex.
The generic answer to your question isn't obvious...
It might be simpler for polygons, particularly convex polygons: you can iterate on the path and find its bounding box by computing the max and min of the x and y coordinates of each point of the path.
Then you can decide that the center of the shape is the center of the of the bounding box.
An alternative is to put an invisible element at what you estimate to be the center (for complex shapes, the concept of "center" can be variable), and get its coordinates to find out where the center is. Particularly for rotating purpose: you might want to do this rotation around a specific point which might not be the geometrical center.
The issue we are trying to solve the issue of locating a point in two different representations of a plane. The first plane we have is rotated to create perspective; the second is a 2d view of that same plane. We have 4 points on each of the plans that we know to be equivalent. The question is if we have an arbitrary point in plane 1, how do we find the corresponding point in plane 2?
It is best probably to illustrate the use case in order to best clarify the question. We have an image illustrated on the left.
Projective plane
2D layout diagram of space
So the givens that we have are the red squares from both pictures. Note that if possible, I’d like it to be possible that the 2D space isn’t necessarily a square. These are available to us ahead of time and known. I also have green dots laid out on the plane in the first image. I’d like to be able to do a projection of the dot in image 1 onto the space in image 2.
Note also for the image 1 I do not have a defined window or eye position. I just know that the red square from image 1 is a transform of the red square form image 2 and that the image 2 is in 2D space.
This is a special case of finding mappings between quadrilaterals that preserve straight lines. These are generally called homographic or projective transforms. Here, one of the quads is a square, so this is a popular special case. You can google these terms ("quad to quad", etc) to find explanations and code, but here are some for you.
Perspective Transform Estimation
a gaming forum discussion
extracting a quadrilateral image to a rectangle
Projective Mappings for Image Warping by Paul Heckbert.
The math isn't particularly pleasant, but it isn't that hard either. You can also find some code from one of the above links.
Update
And this is one of my favorites: Computing a projective transformation