I am trying to train a stable diffusion model, which receives 512 x 512
images as inputs.
I am downloading the bulk of images from the web, and they have multiple sizes and shapes, and so I need to preprocess them and convert to 512 x 512
.
If I take this 2000 × 1434
image:
And I try to resize it, with:
from PIL import Image
# Open an image file
with Image.open("path/to/Image.jpg") as im:
# Create a thumbnail of the image
im.thumbnail((512, 512))
# Save the thumbnail
im.save("path/to/Image_resized.jpg")
I get this 512 × 367
image:
But I need 512 for both width and height, without distorting the image, like you can achieve on this website:
Any ideas on how I can achieve this conversion using python?
I dont think a resize of an image with another aspect ratio of 1:1 (512:512) is possible without distorting the image. You can resize the shorter dimension of the image to 512px and crop the large dimension to 512px.
from PIL import Image
# Open an image file
with Image.open("image.jpg") as im:
width, height = im.size
if width < height:
newWidth = 512
newHeight = int(height / (width / 512))
cropTop = (newHeight - 512) // 2
cropBottom = cropTop + 512
crop = (0, cropTop, 512, cropBottom)
else:
newHeight = 512
newWidth = int(width / (height / 512))
cropLeft = (newWidth - 512) // 2
cropRight = cropLeft + 512
crop = (cropLeft, 0, cropRight, 512)
imResize = im.resize((newWidth, newHeight))
imCrop = imResize.crop(crop)
imCrop.save("image_resized_cropped.jpg")