I’m currently trying to create a conical gradient, and it kind of works. However, it doesn’t look quite right and I can’t wrap my hand around to why: The line that goes up from the center is slightly angled to the right and at the bottom there is a visible (not too noticable) line. Code is as follows: Oh, and
Tag: python-imaging-library
Does Image.open() distort grayscale PNG images?
Recently, I’ve been trying to load some grayscale images into my Python program using Pillow’s Image.open(). However, I’ve been finding that the image gets distorted, and all the values polarized. This is the image generated by the Mac preview: And, this is the image generated by the Image.open() function: My code is as follows: And, the characteristics of the image
PyQt5: Python crashes with SIGSEGV *sometimes* when sending pixmap via a signal from another thread
Background and Issue I am trying to process streaming data from a camera. Python keeps crashing with this message though: The crash happens sometimes while emitting the signal containing an image. My code, shown below, follows this process: A QObject named CameraThread is instantiated within the GUI and is run by a QThread. CameraThread instantiates a class IngestManager and gives
How to return a list of PIL image files from fastapi response?
I have created an rest-api using fastapi, which takes a document (pdf) as input and return a jpeg image of it, I am using a library called docx2pdf for conversion. This is the output of doc_results, basically a list of PIL image files If I run my current code, it is returning the doc_results as json output and I am
How to decrease Image object size that dumped through pickle in Python
I’m working on a socket data transfer project. I want to watch client screen. I’m using pillow and pickle module both server and client but when I trying to send ImageGrab.grab() object, object size is 3Mb. It’s very high data for transferring. Although object size is 3MB, saved size (ImageGrab.grab().save(“example.jpg”)) is 200 kb. When i save file then read saved
How to apply an operation to every PIXEL (not every rgb component!) of a python image (either using numpy, opencv or PIL)?
I’m trying to apply a function over all pixels of an image (in my specific case I want to do some colour approximation per pixel, but I don’t think this is relevant for the problem) in an efficient way. The thing is that I’ve found different approaches to do so, but all of them apply a function over each component
How to display image with upload button in and resize it with window resize (Dynamically)with Tkinter python, I need to add upload button
I need to add upload button so that I can upload the picture and display with this class. Everything working but when I am adding the upload button its giving me some error and my code is not wokring. Answer Create the Button widget within the class constructor and bind it with self.loadbackground. Also, you don’t need to recreate the
PYTHON: Extracting data from .xlsx using pandas ExcelWriter and outputting as text on image using PIL
1 / Data: 2 / Set-up (pandas): 3 / Formatting (e.g. for first row): 4 / Once accomplished, the data needs to be printed on an image. Set-up (PIL): 5 / Finished product: ^ This is an example of the output of row #1 (if successful), what am I missing here? How can I loop it? Thanks in advance! Answer
How to overlay two non-transparent images in Pillow
I’m trying to make a simple image manipulation function that applies a soviet flag filter to a profile picture. Both pictures are non-transparent. I have some code That would work if either of the images were transparent. However, because my images are not transparent, it just shows the background. Also, the pictures have different resolutions, so it just shows the
Reshape 5-dimensional tiled image to 3-dimensional normal image
I’m creating a program that takes use of an RGB image that is tiled of the shape (n, n, 3, l, l). n is the number of each tile on each side of the image, and l is the length of each tile in pixels. I am trying to reshape this into a (3, l * n, l * n)