I try to run this code for 3D face reconstruction from github, the image result is combination of three images ( original image, reconstructed face image ,and reconstructed face with landmarks) I fail to save or display only the reconstructed face image.
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I am reading a image using open cv and when it shows the image it zooms it in. The image is 1080 x 1257. I also tried another image with dimension 5961 x 3059 it zooms it in even more. If I use img=cv2.imread("hello.jpg",50)
it shows the first image in original dimension but is of grayscale, but the second image is still not in original dimension. So how do I display original dimension images
Help me with this as am I an absolute beginner with OpenCV.
here is the second image I was talking about.
here is the output of the image
img=cv2.imread("rainbow.png",0)
cv2.imshow('israinbow',img)
cv2.waitKey(5000)
cv2.destroyAllWindows()
today I treid a python filtering code that supposes to increase the noise in the image(de-noising) for a gray-scale image(medical image) and it's for a skull, the problem is i keep getting colored pixels, i mean the noise increased in terms of colored image, not in grayscale so please help me to make the code filter in gray-scale mode, extra details :
the code :
enter link description to see the filter code
original image :
the de-noised image after applying noise filter :
you can see the problem clearly that when i zoom into the picture i can see the colored pixels, while it supposes to be a gray-scale form
colored pixels in the filtered image :
partial zoom in
full zoom in
so please guess does anybody knows how to edit that code so that it can increase the noise in form of grayscale mode.
Your input image is a 3-channel JPEG. Make it greyscale (1 channel) before applying noise then it won't be able to treat the channels differently because there will only be one.
img.transform_colorspace('gray')
I am trying to do iris segmentation using python. After doing some thresholding, in this process I want to get the black circle area (which is pupil) in the image that I attached, is there any process or method that I can get only the black circle area from the image? Eyes Image that already thresholded
This is the original image
Original Image
I am performing Thinning operation on Gujarati character using neural networks. after train neural network I get the blurred image. SO, I want the Thinned image from blur image.The blurred image has the medial pixel of the stroke is much brighter than adjacent pixel. so My task is how to extract medial pixel which is part of the thinned image.
here, There are two images give below one is input blur image and the second image is Thinned image which I want from the blurred image. please give me the suggestion.
Input blur image :
Output Image :
I am following the OpenCV Camera Calibration tutorial, I have used about 100 images for the calibration. After getting camera matrix and distance matrix, I use them to undistort other set of images. What I realized is the undistorted image is highly distorted on both sides.
One of the example imgs for camera matrix:
Using the camera matrix to undistort my experimental img gave me very unreasonable results.
Original image:
After applying undistor():
Clearly, the undistortion process only paid attention to the center of the image. How can I make it undistort the image properly?
Thank you very much!
UPDATE:
Using images to cover the Filed of View as much as possible helps. Here is the new result of the same image:
I have one more question: How to know if the calibration returns satisfying calibration results? RMS is a parameter. However, it is not very robust.