So I have been using this code,. I am trying to generate the raw mask of the images from COCO dataset. But what i get is some thing like this But what I want is something like this How can I get the raw mask against each image ? Answer I’m late to the party, but if this can help
Tag: image-processing
How can i display my images and draw rectangles over regions of interests and get the coordinates?
What i want is to read an image and have it fixed on the screen, then manually draw rectangles on the regions of interest and have them outputed as coordinates of the rectangle as have the rectangle stay on the image to know which region of interest i marked. The first step is actually reading the image and fixing it
Replace the color of block in gray scale image in Python
I have an Image of 128×128 pixels in which, there are 1024 blocks of 4×4 pixels each. If the coordinates of the first block areblock1= im[0:4, 0:4], then I want to replace the colour of pixels into a specific pixel intensity(or colour),example-128. So what I want to do is I want to change the colour of the image something like
Divide the image into 4×4 blocks and save each coordinate in variable
I have an grayscale Image of 128×128 that I want to divide into 4×4 pixel non-overlapping blocks and I want to save coordinate of each pixel as variable like this- I know I can do it manually by defining variables, but I can use any for loop for making it faster? After that, I’ll find mean of each block by-
Reconstruct Image from patches/tiles in python
I have a task where I have tiled an Input image using the code: After that I calculated the sum of all tiles and sort them in ascending order. I’ll take the sum.sorted[-20] as a threshold and set all tiles below that threshold to 0 in order to neglect background. So far everything works fine. Now I need to reconstruct
Create an image using the pixels median fom other images
I have six images and I want to find the median of each pixel and create a new pic from it. I created a list of my images in this manner: and then I wrote a for loop like that: I’ve found that there’s a function that finds the median using numpy but I don’t know how to use it.
Resize image to maintain aspect ratio in Python, OpenCv
I’d like to get a 1000 x 1000 picture in Python from any input picture so that the input doesn’t lose it’s aspect ratio. In other words, I want to resize the input so that its longer dimension is 1000 pixels and “fill” the other dimension with the background color until it become 1000 x 1000 square. The original one
Python open jp2 medical images – Scipy, glymur
I am trying to read and tile a jp2 image file. The image is RGB 98176 x 80656 pixels (it is medical image data). When trying to read the image with glymur I get this error: I understand the image is too big. What I need is to read the image data by tiles and save them elsewhere and in
“SystemError: tile cannot extend outside image” in PIL during save image
I have this Image => here is, all coordinates of above yellow boxes that is written in 3.txt file. My intension is to crop those boxes and save all boxes as Image. I have written a code for that but getting error. Here is my code => I am getting these error => Traceback (most recent call last): File “reshape.py”,
python – opencv morphologyEx remove specific color
After remove captcha’s background. The image remain digits and noise. Noise line is all in one color : RGB(127,127,127) And then using morphology method. Some part of digit will be remove. How to use morphologyEx() remove only color in RGB(127,127,127) ? Answer In order to eliminate color within a particular range you have to use cv2.inRange() function. Here is the