Image = image.resize((width_size, fixed_height), ) Width_size = int((float(image.size) * float(height_percent))) Height_percent = (fixed_height / float(image.size)) We will use height and width values by proportioning them to fixed height. You can see that our “image.size” code gives us a tuple. To protect pictures’ image and width ratio during resizing process, we need to determine a base width for our script. How to Resize Images in a Fixed Aspect Ratio with Python’s PIL Library How to Resize Multiple Images in bulk with Python and Pillow How to Create Thumbnail Image with a Fixed Aspect Ratio in Python’s Pillow Library We can change an image’s size or shape very easily thanks to Pillow. PIL and Image from PIL are for opening, changing and saving images with different optimization options. OS and Glob Modules for the showing absolute path of our Python file so that we can use shorter file names. If you didn’t download Pillow before, you can use the code below: pip install pillowįirst, we need to import libraries: from PIL import Image Like in the Image Compression article, we will use Pillow Library (Python’s Image Library) for image compression. I recommend you to examine the pixel quality so that you can see the capacity of the Image optimization in scale via Python. Note: Images on this content are not compressed so that the differences between optimized-resized and non-optimized/resized ımages can be seen clearly. For multiple images compression in bulk with Python, you can read our complete guideline. In this article, we will focus on how to resize multiple images in bulk with Python. Because of those motivations, Image Compression Algorithms are developed every year. ![]() Here's a python script that uses this function to run batch image resizing.Image manipulation, optimization and resizing or downscaling, color type changing, or other kinds of image-related processes have value for SEO, UX, Page Speed, and Bandwith. Print('writing to disk'.format(out_f_path)) Img = img.resize((max_px_size, hsize), Image.ANTIALIAS) Hsize = int(float(height_0) * float(wpercent)) Out_f_path = os.path.join(output_folder, out_f_name) Not the prettiest but gets the job done and is easy to understand: def resize(img_path, max_px_size, output_folder): Return img.resize(size_new, resample=Image.LANCZOS)Ī simple method for keeping constrained ratios and passing a max width / height. If img_ratio = video_ratio: # image is not tall enough Width, height = video_size # these are the MAX dimensions So after I couldn't find an obvious way to do that here (or at some other places), I wrote this function and put it here for the ones to come: from PIL import Imageĭef get_resized_img(img_path, video_size): The Image.thumbnail method was promising, but I could not make it upscale a smaller image. I was trying to resize some images for a slideshow video and because of that, I wanted not just one max dimension, but a max width and a max height (the size of the video frame).Īnd there was always the possibility of a portrait video. I hope it might be helpful to someone out there! I tried to document it as much as I can, so it is clear. # Enter the name under which you would like to save the new imageĪnd, it is done. ![]() # resample filter ->, (default),, etc. #new_width = round(new_height * asp_rat) # uncomment the second line (new_width) and comment the first one (new_height) # NOTE: if you want to adjust the width to the height, instead -> Img = img.resize((new_width, new_height), Image.ANTIALIAS) Img = Image.open(img_path) # puts our image to the buffer of the PIL.Image object You do not need the semicolons ( ), I keep them just to remind myself of syntax of languages I use more often. In this case, it will adjust the height to match the width of the new image, based on the initial aspect ratio, asp_rat, which is float (!).īut, to adjust the width to the height, instead, you just need to comment one line and uncomment the other in the else loop. I will also add a version of the resize that keeps the aspect ratio fixed.
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