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Matplotlib scaling an image when saving a converted dxf as PDF

I am currently converting a dxf drawing that I made, to a pdf drawing using the function described here: Python converting DXF files to PDF or PNG or JPEG. (I am also putting the code below)
The problem is, that when I convert to the pdf, the code automatically scales the drawing to make it fit to a certain size. Now I need to either turn this off, or have a way of knowing what the scaling factor that it used was.
The complete code is as follows:
import matplotlib.pyplot as plt
import ezdxf
from ezdxf.addons.drawing import RenderContext, Frontend
from ezdxf.addons.drawing.matplotlib import MatplotlibBackend
# import wx
import glob
import re
class DXF2IMG(object):
default_img_format = '.png'
default_img_res = 300
def convert_dxf2img(self, names, img_format=default_img_format, img_res=default_img_res):
for name in names:
doc = ezdxf.readfile(name)
msp = doc.modelspace()
# Recommended: audit & repair DXF document before rendering
auditor = doc.audit()
# The auditor.errors attribute stores severe errors,
# which *may* raise exceptions when rendering.
if len(auditor.errors) != 0:
raise exception("The DXF document is damaged and can't be converted!")
else :
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1])
ctx = RenderContext(doc)
ctx.set_current_layout(msp)
ctx.current_layout.set_colors(bg='#FFFFFF')
out = MatplotlibBackend(ax)
Frontend(ctx, out).draw_layout(msp, finalize=True)
img_name = re.findall("(\S+)\.",name) # select the image name that is the same as the dxf file name
first_param = ''.join(img_name) + img_format #concatenate list and string
fig.savefig(first_param, dpi=img_res)
if __name__ == '__main__':
first = DXF2IMG()
first.convert_dxf2img(['test.DXF'],img_format='.pdf')

From the github discussion thread: https://github.com/mozman/ezdxf/discussions/357
This can be solved in a way that isn't specific to ezdxf by carefully setting the figure size before saving. Matplotlib is quite complex when it comes to measurements. I have a solution which seems to work well but there may be slight inaccuracies since the calculations are done using floating point numbers but at the end of the day pixels are a discrete measurement so it's probably possible to be at least 1 pixel off. There are probably lots of other things like line widths which have an effect. ... you can calculate the desired figure size by specifying a desired units_to_pixels conversion factor and scaling the figure size so that the data spans the correct number of pixels. This assumes that the figure aspect ratio is already correct as my solution uses the same scale factor for width and height.
There's an extended workaround at the page I linked. Rather than copy-paste it here, I think the whole response is worth reading.

Programming a picture maker template in Python possible?

I'm looking for a library that enables to "create pictures" (or even videos) with the following functions:
Accepting picture inputs
Resizing said inputs to fit given template / scheme
Positioning the pictures in pre-set up layers or coordinates
A rather schematic approach to look at this:
whereas the red spots are supposed to represent e.g. text, picture (or if possible video) elements.
The end goal would be to give the .py script multiple input pictures and the .py creating a finished version like mentioned above.
Solutions I tried were looking into Python PIL, but I wasn't able to find what I was looking for.

Yes, it is possible to do this with Python.
The library you are looking for is OpenCV([https://opencv.org][1]/).
Some basic OpenCV python tutorials (https://docs.opencv.org/master/d9/df8/tutorial_root.html).
1) You can use imread() function to read images from files.
2) You can use resize() function to resize the images.
3) You can create a empty master numpy array matching the size and depth(color depth) of the black rectangle in the figure you have shown, resize your image and copy the contents into the empty array starting from the position you want.
Below is a sample code which does something close to what you might need, you can modify this to suit your actual needs. (Since your requirements are not clear I have written the code like this so that it can at least guide you.)
import numpy as np
import cv2
import matplotlib.pyplot as plt
# You can store most of these values in another file and load them.
# You can modify this to set the dimensions of the background image.
BG_IMAGE_WIDTH = 100
BG_IMAGE_HEIGHT = 100
BG_IMAGE_COLOR_DEPTH = 3
# This will act as the black bounding box you have shown in your figure.
# You can also load another image instead of creating empty background image.
empty_background_image = np.zeros(
(BG_IMAGE_HEIGHT, BG_IMAGE_WIDTH, BG_IMAGE_COLOR_DEPTH),
dtype=np.int
)
# Loading an image.
# This will be copied later into one of those red boxes you have shown.
IMAGE_PATH = "./image1.jpg"
foreground_image = cv2.imread(IMAGE_PATH)
# Setting the resize target and top left position with respect to bg image.
X_POS = 4
Y_POS = 10
RESIZE_TARGET_WIDTH = 30
RESIZE_TARGET_HEIGHT = 30
# Resizing
foreground_image= cv2.resize(
src=foreground_image,
dsize=(RESIZE_TARGET_WIDTH, RESIZE_TARGET_HEIGHT),
)
# Copying this into background image
empty_background_image[
Y_POS: Y_POS + RESIZE_TARGET_HEIGHT,
X_POS: X_POS + RESIZE_TARGET_WIDTH
] = foreground_image
plt.imshow(empty_background_image)
plt.show()

Overlaying coloured pixels on top of an image using Python Imaging Library

Okay, first thing first. This is a near duplicate of this question.
However, the issue I am facing is slightly different in a critical way.
In my application, I read a generic file name in, load said image, and display it. Where it gets tricky is I have overlay the appearance of being 'highlighted'. To do this, I was using the Image.blend() function, and blending it with a straight yellow image.
However, when dealing with blend, I was fighting the error that the two images are not compatible to be blended. To solve this, I opened the sample image I had in paint, and just pasted yellow over the whole thing, and saved it as a copy.
It just occurred to me that this will fail when a different type of image is read in by file name. Remember this needs to be generic.
So my question is: Instead of making a copy of the image manually, can I get python to generate one by copying the image and modifying it so it is solid yellow? Note: I do not need to save it after, so just making it happen is enough.
Unfortunately, I am not allowed to share my code, but hopefully the following will give an idea of what I need:
from PIL import Image
desiredWidth = 800
desiredHeight = 600
primaryImage = Image.open("first.jpg").resize((desiredWidth, desiredHeight), Image.ANTIALIAS)
# This is the thing I need fixed:
highlightImage = Image.open("highlight.jpg").resize((desiredWidth, desiredHeight), Image.ANTIALIAS)
toDisplay = Image.blend(primaryImage, highlightImage, 0.3)
Thanks to anyone who can help.

Sounds like you want to make a new image:
fill_color = (255,255,0) #define the colour as (R,G,B) tuple
highlightImage = Image.new(primaryImage.mode, #same mode as the primary
primaryImage.size, #same size as the primary
fill_color)#and the colour defined above
this creates a new image with the same mode and size as the already opened image, but with a solid colour. Cheers.
Also if you are using Pillow instead of original PIL you can even get the color by name:
from PIL.ImageColor import getcolor
overlay = 'yellow'
fill_color = getcolor(overlay, primaryImage.mode)

Working with truncated images with PIL

I am trying to get the Python 2.7 PIL Library to work with JPEG images that are only available as a stream coming from a HDD image and are not complete.
I have set the option:
ImageFile.LOAD_TRUNCATED_IMAGES = True
And load the stream as far as it is available (or better said: as far as I am 100% sure that this data is still a image, not some other file type). I have tested different things and as far as I can tell (for JPEGs) PIL only accepts it as a valid JPEG Image if it finds the 0xFFDA (Start of Scan Marker). This is a short example of how I load the data:
from PIL import Image
from StringIO import StringIO
ImageFile.LOAD_TRUNCATED_IMAGES = True
with open("/path/to/image.raw", 'rb') as fp:
fp.seek("""jump to position in image where JPEG starts""")
data = fp.read("""number of bytes I know that those belong to that jpeg""")
img = Image.open(StringIO(data)) # This would throw exception if the data does
# not contain the 0xffda marker
pixel = img.load() # Would throw exception if LOAD_TRUNCATED_IMAGES = false
height,width = img.size
for i in range(height):
for j in range(width):
print pixel[i,j]
On the very last line I expected (or hoped) to see at least the read pixel data to be displayed. But for every pixel it returns (0,0,0).
The Question: Is what I am trying here not possible with PIL?
Some weeks ago I tried the same with a image file I truncated myself, simply by cutting data from it with an editor. It worked for the pixel-data that was available. As soon as it reached a pixel that I cut off, the program threw an exception (I will try this again later today to make sure that I am not remembering wrong).
If somebody is wondering why I am doing this: I need to make sure that the image/picture inside that hdd image is in consecutive blocks/clusters and is not fragmented. To make sure of this I wanted to use pixel matching.
EDIT:
I have tried it again and this is what I have seen.
I opened a truncated image in GIMP and it showed me a few pixel lines in the upper part, but PIL was not able to at least give me the RGB values of those pixels. It always returns (0,0,0).
I made the image slightly bigger such that the lower 4/5 of the image was not visible, but that was enough for PIL to show me the RGB values that were available. Everything else was (0,0,0).
I am still not 100% sure whether PIL can show me the RGB values, even if only view pixel-data is available.

I would try it with an uncompressed format like TGA. JPG being a compressed format may not make any sense to extract pixels from an incomplete image. JPEG actually stores the parameters for equations that describe the image, not pixel values. When you query a JPEG for a pixel value it evaluates the equations at that point and returns the result.

I have the same problem with Pillow==9.2.0
Let's downgrade to Pillow==8.3.2 and it works.

I don't really know about streaming, but I think that you simply cannot access rgb value the way you do.
Try:
rgb_im = img.convert('RGB')
r, g, b = rgb_im.getpixel((i, j))

PyGame image save colors distorted

So I have implemented the following screenshot functionality into my game just to log progress and stuff like that. This is my code:
pygame.image.save(screen, save_file)
Pretty basic. I recently upgraded to python 3.3 and have since been having the issue of distorted colors using this function. Here is what I mean:
Distorted Color:
So it looks quite nice, but it isn't how it supposed to be. This is the actual image:
Is this a known issue or is it just me? Are there any fixes to it or is it just a broken function at the moment. I am using pygame 1.9.2pre and I am assuming it is just a bug with the pre release but I was having issues using any other versions of pygame with python 3.3.

Some users have reported difficulty with saving images as pngs:
I only get .tga files even when I specify .png. Very frustrating.
If you use .PNG (uppercase), it will result in an invalid file (at least on my win32). Use .png (lowercase) instead.
PNG does not seem to work, I am able to get a preview of it in Thunar, but everywhere else It says that it is not a valid PNG.
Saving in a different format may be helpful. For example, BMP is a simple format, so it's unlikely that Pygame's implementation will be buggy.
If you really want to save as PNG, you can reverse the distortion by swapping the red channel with the green one. This is fairly easy. For example, using PIL:
from PIL import Image
im = Image.open("screenshot.png")
width, height = im.size
pix = im.load()
for i in range(width):
for j in range(height):
r,g,b = pix[i,j]
pix[i,j] = (g,r,b)
im.save("output.png")
Or you can save as BMP and convert to PNG after the fact:
from PIL import Image
im = Image.open("screenshot.bmp")
im.save("screenshot.png")

for future reference, this trick worked for me:
from PIL import Image
imgdata = pygame.surfarray.array3d(screen).transpose([1,0,2])[:,:,::-1]
Image.fromarray(imgdata).save('output.png')