So I have about 12000 image links in my SQL table. Point is to detect which of those images contain watermarked text and which don’t. All text and borders is like this. I’ve tried with OpenCV and tesserocr But doesn’t seem it recognizes text on image at all. My second approach was to use some external open API site. It
Tag: image-processing
How to resize a depth map from size [400,400] into size [60,60]?
I have a depth map image which was obtained using a kinect camera. In that image I have selected a region of size [400,400] and stored it as another image. Now, I would like to know how to resize this image into a size of [x,y] in python. Answer Same as a normal image
Filter in opencv/python
I am trying to learn filters in opencv and running this code. But the problem is that when ı run the code it gives me an almost dark image and warns me with “c:/Users/fazil/Desktop/Yeni Metin Belgesi (3).py:19: RuntimeWarning: overflow encountered in ubyte_scalars result[j,i,a]=int((image[j,i,a]+image[j,i-1,a]+image[j,i+1,a]+image[j+1,i,a]+image[j-1,i,a]+image[j+1,i+1,a]+image[j+1,i-1,a]+image[j-1,i-1,a]+image[j-1,i+1,a])/9)”. And if ı comment these out and run code with the lines working with cv2.filter2d method it
Manual registration with SimpleElastix
I’m using SimpleElastix (https://simpleelastix.github.io/) for the registration (Affine) of the two 2D images (see attached) . For this I’m using this code : After the execution of the latter, I obtain the following TransformParameters0.txt that contains the transformation matrix : My aim is to use this matrix-tranformation to register the floating image and get a registrered image similar to the
ImageDataGenerator() for CNN with input and output as an Image
I’m looking for a training map with something like this: Grayscale Image -> Coloured Image But the dataset can’t be loaded all to the ram as X and Y because of obvious reasons. I looked up the ImageDataGenerator() library, but it didn’t give me a clear answer as to make it work here. Summary: Input Shape = (2048, 2048, 1)
Image Processing w. Cloud Solution [closed]
Closed. This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 2 years ago. Improve this question preface I would like to learn more about cloud computing. After being laid off in July due to Covid and
Extract N number of patches from an image
I have an image of dimension 155 x 240. Like the following: I want to extract certain shape of patchs (25 x 25). I don’t want to patch from the whole image. I want to extract N number of patch from non-zero (not background) area of the image. How can I do that? Any idea or suggestion or implementation will
Pinch/bulge distortion using Python OpenCV
I want to apply a pinch/bulge filter on an image using Python OpenCV. The result should be some kind of this example: https://pixijs.io/pixi-filters/tools/screenshots/dist/bulge-pinch.gif I’ve read the following stackoverflow post that should be the correct formula for the filter: Formulas for Barrel/Pincushion distortion But I’m struggling to implement this in Python OpenCV. I’ve read about maps to apply filter on an
Improving image deskew using Python and OpenCV
The code I’ve produce to detect and correct skew is giving me inconsistent results. I’m currently working on a project which utilizes OCR text extraction on images (via Python and OpenCV), so removing skew is key if accurate results are desired. My code uses cv2.minAreaRect to detect skew. The images I’m using are all identical (and will be in the
Canny edge detection not working on Gaussian blurred images
I am trying to detect edges on this lane image. First blurred the image using Gaussian filter and applied Canny edge detection but it gives only blank image without detecting edges. I have done like this: Answer You should always examine your data. Simply running your script step by step and examining intermediate values shows what is going wrong: mpimg.imread