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I'm trying to implement an algorithm detecting and counting number of hairs. The main idea is described as below:
Enhance Image by applying Contrast Stretching.
Segment image.
Do thinning segmented image.
Detect Line by HoughLine Transform and Relaxation.
The implementation is based on Opencv/C++. However, since Thinning algorithm doesn't perform accurately, it leads to wrong result when I apply HoughLine, especially in case of overlap or touching hair. Moreover HoughLine is sensitive with parameters. If you have other ideas, please help me. Thank you very much.
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I'm using YOLO to detect people in a video stream from camera and would like to "map" founded bonding boxes onto 2D plan of the room.
Could you please give me a hint which algorithms might be used for it?
The idea is shown on the picture from the github repository, but I need not to measure distance but "project" an object position on 2D map of the room
https://github.com/sassoftware/iot-tracking-social-distancing-computer-vision
Using 3D cameras or just 2 regular ones might help a lot as well
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I wrote a 2d simulation (very similar to the Atari- OpenAi games) in pygame, which I need for an reinforcement learning project. I'd like to train a neural network using mainly image data, i.e. screenshots of the pygame gameboard.
I am able to make those screenshots, but:
- Is possible to gather this image data - or, more precisely, the
corresponding rgb image matrix - also without rendering the whole
playing ground to the screen?
As I figured out there is the possibility to do such in pyglet ... But I would like to avoid to rewrite the whole simulation.
Basically, yes. You don't have to actually draw anything to the screen surface.
Once you have a Surface, you can use methods like get_at, the PixelArray module or the surfarray module to access the RGB(A)-values of each pixel.
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Can we achieve this with SKPhsyicsBody? I already did some research, and knew SpriteKit physics body does handle irregular shapes like curves. But there's no mentioning that the SKNote's rotation angle will dynamically change like the example game provided (made with unity) in the image. It would be a really bad experience for players when the main element of the game does not follow the curve with its rotation.
Yes, yes you can. And yes, yes it will (rotate with contact). All possible, all permitted and all exactly how the physics bodies interact. This is simply a matter of setting friction properties between the surface (ground) and your hero's ski in conjunction with gravity so it provides your idealised experience.
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I need to calculate the color histogram of images in order to get a feature for finding similarity between images.
(description: https://stackoverflow.com/a/844113/5142270 and https://en.wikipedia.org/wiki/Color_histogram).
The only problem I am facing is in deciding how to scale the images so that they will have the same number of pixels. Is there a standard image size(in pixels) that is used by researchers for this purpose, when there are thousands of images that can be of any dimension? I tried searching a lot on how to scale the images, but was unable to find out what was supposed to be done.
Thanks in advance.
You can try using pyramids.
You basically don't have 1 'golden number' of pixels, but you do your feature finding on an image 1/2 the size, and 1/4 and 1/8 and so on, so your feature detection will not be size dependent.
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Is it possible to use a couple of webcams (or any camera for that matter) to get the x, y and z co-ordinates of an object and then track them perhaps using OpenCV as it moves around a room.
I'm thinking of it in relation to localising and then controling an RC helicopter.
Yes. You need to detect points on both images simultaneously and then match the pairs that correspond to the same point in the scene. This way you will have the same point represented by different coordinate spaces (camera 1 and camera 2).
You can start here.
If using depth sensor is acceptable then you can take a look at how ReconstructMe does it. Otherwise take a look at this google search.