contour | Contour is a Kubernetes ingress controller using Envoy | Load Balancing library

This is a perfect sample image that includes range of black objects.

And this code suppose to find every black plants

I am working with the R programming language. I made the following 3 Dimensional Plot using the "plotly" library:

I am trying to make a simple contour plot.

I am newbie to OpenCV. I'm trying to find the contours of the captcha image. It does not work only when my captcha image contains the dotted text.

I have done following code for that:

I want to remove the background, and draw the outline of the box shown in the image(there are multiple such images with a similar background) . I tried multiple methods in OpenCV, however I am unable to determine the combination of features which can help remove background for this image. Some of the approaches tried out were:

• Edge Detection - Since the background itself has edges of its own, using edge detection on its own(such as Canny and Sobel) didnt seem to give good results.
• Channel Filtering / Thresholding - Both the background and foreground have a similar white color, so I was unable to find a correct threshold to filter the foreground.
• Contour Detection - Since the background itself has a lot of contours, just using the largest contour area, as is often used for background removal, also didnt work.

I would be open to tools in Computer Vision or of Deep Learning (in Python) to solve this particular problem.

How can I determine the confidence/credibility intervals for the posterior estimates of a multi-parameter model?

I can get the confidence interval for each parameter separately. (Currently using bayestestR, but I don't mind using something else)

I have implemented a simple randomized, population-based optimization method - Grey Wolf optimizer. I am having some trouble with properly capturing the Matplotlib plots at each iteration using the camera package.

I am running GWO for the objective function f(x,y) = x^2 + y^2. I can only see the candidate solutions converging to the minima, but the contour plot doesn't show up.

Do you have any suggestions, how can I display the contour plot in the background?

GWO Algorithm implementation

I need to make a OMR detection system using Python for my High School Vacation Project(which potentially might be used by the school to some extent if it is reliable enough) , I have done quite a bit of research on it , and have tried out everything from contours to template matching, I feel template matching works fine but it can only detect one circle out of many in the OMR sheet, can someone help me in figuring out how I can detect multiple(all) circles(irrespective of whether they are bubbled or not), in the omr sheet and their respective coordinates , that would be enough for me.

What I have tried:

Below is a figure I have created for a single set of data, with contours plotted over the top. This is exactly what I need, I just need it plotting as a series of subplots for my 7 model runs, with the colourful salinity data, and the contours plotted over the top.

However, when I try to do the subplots, I can get in the salinity data, but I cannot plot the contours on top (or the colorbar, but that's another issue). Ideally, this should look like 7 mini versions of figure 1. However, I get the following error: