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When loading and writing a PNG image to PDF using Pillow (PIL), how do I fix the size of the image in the PDF?

I am reading in a list of PNG images from a directory and I want to maintain the image sizes.
However, when I go to save them, each image is automatically resized to fit the entire page AND it automatically rotates the images to landscape rather than keeping them portrait.
Example of what I am doing below:
from PIL import Image
x = []
# get list of images
for i in [list of image files in my directory]:
im = Image.open(i)
im = im.convert('RGB') # will not save as RGBA
x.append(im)
im.save('my_doc.pdf', save_all=True, append_images=x)
Yet, the images which are all the same dimensions and sized to fit neatly onto a single page in portrait orientation, are being rotated to landscape orientation and stretched to the limits of the page making them blurry as a result.
I want one image per page, using the native dimensions of the images, and in portrait.
Is there a way to prevent PIL from doing this?
Thanks in advance!

Is there a way to increase the size of the background image in turtle?

I am trying to make a game in python 3 which requires a background image. I already have the image. The problem here is my image looks small compared to the big screen. I don't want to change the size of the screen because then I would have to redo all the coordinates of the other objects on the screen. Is there any way I can increase the size of the background image?
Ps. I'm using Python 3 and on VS code.
Thanks in advance!
This is the picture of what the small picture looks like.enter image description here

In order to increase the size of the image, you would need too increase the resolution.
Assuming that you are using windows, open the png with Microsoft Photos, and click on the three horizontal dots at the top right.
A dropdown menu will open, press the third option from the top labeled "Resize"
After this, press on "Define custom dimensions" and you may manipulate the dimensions of the image as you like.
Then, simply save the resized image, and use it in your project.

you can also do this using CV2 library
import cv2
image=cv2.imread("image.png")
scale_percent=1.5
width=int(image.shape[1]*scale_percent)
height=int(image.shape[0]*scale_percent)
dimension=(width,height)
resized = cv2.resize(image,dimension, interpolation = cv2.INTER_AREA)
print(resized.shape)
cv2.imwrite("output.png",resized)
OR you can use PIL library as well
from PIL import Image
image = Image.open("image.png")
image.save("output.png", dpi=(image.size[0]*1.5,image.size[1]*1.5))

How to save grayscale image in Python?

I am trying to save a grayscale image using matplotlib savefig(). I find that the png file which is saved after the use of matplotlib savefig() is a bit different from the output image which is showed when the code runs. The output image which is generated when the code is running contains more details than the saved figure.
How can I save the output plot in such a manner that all details are stored in the output image?
My my code is given below:
import cv2
import matplotlib.pyplot as plt
plt.figure(1)
img_DR = cv2.imread(‘image.tif',0)
edges_DR = cv2.Canny(img_DR,20,40)
plt.imshow(edges_DR,cmap = 'gray')
plt.savefig('DR.png')
plt.show()
The input file (‘image.tif’) can be found from here.
Following is the output image which is generated when the code is running:
Below is the saved image:
Although the two aforementioned images denote the same picture, one can notice that they are slightly different. A keen look at the circular periphery of the two images shows that they are different.

Save the actual image to file, not the figure. The DPI between the figure and the actual created image from your processing will be different. Since you're using OpenCV, use cv2.imwrite. In your case:
cv2.imwrite('DR.png', edges_DR)
Use the PNG format as JPEG is lossy and would thus give you a reduction in quality to promote small file sizes. If accuracy is the key here, use a lossless compression standard and PNG is one example.
If you are somehow opposed to using OpenCV, Matplotlib has an equivalent image writing method called imsave which has the same syntax as cv2.imwrite:
plt.imsave('DR.png', edges_DR, cmap='gray')
Note that I am enforcing the colour map to be grayscale for imsave as it is not automatically inferred like how OpenCV writes images to file.

Since you are using cv2 to load the image, why not using it also to save it.
I think the command you are looking for is :
cv2.imwrite('gray.jpg', gray_image)

Using a DPI that matches the image size seems to make a difference.
The image is of size width=2240 and height=1488 (img_DR.shape). Using fig.get_size_inches() I see that the image size in inches is array([7.24, 5.34]). So an appropriate dpi is about 310 since 2240/7.24=309.4 and 1488/5.34=278.65.
Now I do plt.savefig('DR.png', dpi=310) and get
One experiment to do would be to choose a high enough DPI, calculate height and width of figure in inches, for example width_inch = width_pixel/DPI and set figure size using plt.figure(figsize=(width_inch, height_inch)), and see if the displayed image itself would increase/decrease in quality.
Hope this helps.

Image resized with Python PIL are darker

I'm fairly new to PIL and having issue with some image processing. I'm just trying to resize an image to a different resolution using PIL:
resized_hd = image.resize((hd_width, hd_height), Image.ANTIALIAS)
However, the resized picture does not look as good/bright as the original one.
Original (5184*3456) -> http://d31d9cjolqcwln.cloudfront.net/San+Francisco/sutro+baths.jpg
Resized (2048*1366) -> http://d31d9cjolqcwln.cloudfront.net/San+Francisco/HD-sutro+baths.jpg
Any guess ?

I think it's because one of the two images (the original one) has an embedded color profile, which the other one (the resized one) doesn't have. I discovered this by trying to open the original image in gimp. The color profile will cause advanced viewers to make corrections, in theory to fix differences like the ones between paper and screen. When I view the two images in a simple viewer that doesn't know about color profiles, they are really the same brightness. It looks like the PIL library ignores the color profile and doesn't carry it onto the resized image.
I can't help you more precisely than that, though, as I don't know much about color profiles. There might be tools to copy the profile over.

Kuddo to Armin for his suggestion.
Pil allow you to attach an ICC profile to a resized image using the following code:
icc_profile = im1.info.get('icc_profile')
im6 = im1.resize((hd_width, hd_height), Image.ANTIALIAS)
## this one will preserve the colours
im6.save("colorok-"+image,icc_profile=icc_profile)
## this one don't
im6.save("nop-"+image)

PIL - empty PSD image

I'm trying to load this PSD image with Python Imaging Library.
http://www.2shared.com/photo/JjSY7dN-/BG1.html
I'm not very familiar with layered images. Can someone check to see what's the issue? The image appears to be completely transparent. Opening it in my image editor I noticed that the only layer in the image was hidden, I could unhide it to see the colors.
When I load the image with PIL, I get the same issue, but it seems that PIL consolidates the layers into one and I can't do the same as in my image editor. Or maybe there's something I don't know.

PIL provides only very rudimentary hooks into the PSD format. It doesn't support writing or much in the way of manipulation. Your image layer is not shown, so it results in a transparent image. You'll need something more advanced to modify the PSD.
Here's all there is about the PSD format in PIL: http://www.pythonware.com/library/pil/handbook/format-psd.htm
Soon to be available here: http://effbot.org/imagingbook/format-psd.htm