morpholog | Morphological Parser for Russian is able to split words

Like the Title says, I am trying to read an online data file that is in .tbl format. Here is the link to the data: https://irsa.ipac.caltech.edu/data/COSMOS/tables/morphology/cosmos_morph_cassata_1.1.tbl

I tried the following code

I am trying to blur of highest variance point from the image. I wrote code below. 1st part finds the variance of the image. I checked the resultant variance of an image and it is correct. (I used Lena's image) In 2nd part, I find the highest variance coordinates and send to this Function which finds gaussian blur. When I execute this code, it throws "C:\Tmp\blur_highest_variance.py", line 66, in sigma=15) numpy.core._exceptions.UFuncTypeError: Cannot cast ufunc 'subtract' output from dtype('float64') to dtype('uint8') with casting rule 'same_kind' I tried a few conversions between types but no avail. Can you show me some direction?

I used the following code to generate images and then add white noise to finally apply morphological operation (opening) to the final image.

**Question ** - why do I get a different result (Result-1) when I add UINT8 image with UINT8 noise

I tried implementing morphological erosion on digital images with Python. I uploaded a binary image and defined a structural element - ones(3,3). But when I run the code, the following error occurs:

RuntimeError: sequence argument must have length equal to input rank

Please assit. Below are my codes:

In the following microscopy image, I extracted the horizontal white line grid using morphological operators in OpenCV. I couldn't completely get rid of the noise which is why there are some white lines in-between. The grid lines need to be parallel to the x-axis. During the microscopic reading process, perfect parallelism cannot be ensured. In this case, the lines are moving slightly upwards from left to right. How can I realign the lines to the x-axis so that they are parallel to the lower and upper edges of the image using OpenCV or any other Python package?

I'm relatively new to OpenCV so if anyone could give me a hint what operations or functions would be helpful to tackle this problem, I'd be grateful.

Thanks!

I used this function to count objects in segmendted images (I loaded my pretrained weights for prediction)

I am working on a project that aims to extract the "interesting" sequences from an mp4 video using different concepts.

One of them is supposed to be the image entropy and right now, I am a bit stuck.

I have followed this tutorial to get the entropy for a few selected screenshots from the video: https://scikit-image.org/docs/dev/auto_examples/filters/plot_entropy.html

For that, I got results like this one which is what I wanted.

To apply it to my test video, I did the following:

I have been asking several questions for locating and extracting maze from photos on SOF, but none of the answers I get work across different photos, not even across 4 testing photos. Every time when I tweaked the code to make it work for 1 photo, it will fail on the rest of photos due to warped corners/parts or light etc. I feel that I need to find a way which is insensitive to warped image and different intensity of light or the different colors of maze walls(the lines inside a maze).

I have been trying to make it work for 3 weeks without a luck. Before I drop the idea, I would like to ask is it possible to just use Image Processing without AI to locate and extract a maze from a photo? If yes, could you please show me how to do it?

Here are the code and photos:

I am trying to improve this image with the help of morphological operations. The result I get is good but it takes almost 40 seconds to get the resulting image and I was wondering if there is any other method to get a similar or even better result without taking too long.

Below I attach the images and the code that i used to enhance the original image. Thanks

Original spine image Final spine image