I am trying to lower the file size of an image using pillow (pil) however lowering the image quality doesn't lower the size of the saves image.
The saved images 'image2' and 'image3' are the same size.
import PIL from Image
im = Image.open('image.png')
im.save('image2.png', quality=100)
im.save('image3.png', quality=10)
The PNG format only supports lossless compression, for which the compression ratio is usually limited and not freely adjustable.
If I am right, there is a variable parameter that tells the compressor to spend more or less time finding a better compression scheme. But without a guarantee to succeed.
You have to use image compression to reduce sizes - pngquant or similar
https://pngquant.org/
Related
I have a problem_page such that
from PIL import Image
problem_page = "/home/rajiv/tmp/kd/pss-images/f1-577.jpg"
img = Image.open(problem_page)
results in
PIL.Image.DecompressionBombError: Image size (370390741 pixels) exceeds limit of 178956970 pixels, could be decompression bomb DOS attack.
I'd like to respect the limit and not increase the limit (as described here: Pillow in Python won't let me open image ("exceeds limit"))
How can I load it in a way that the resolution is lowered just below the limit and the lower resolution image is referenced in img without causing any error.
It'd be great to have a Python solution but if not, any other solution will work too.
Update(to answer questions in comments):
These images are derived from PDFs to do machine learning(ML). These PDFs come from outside the system. So we have to protect our system from possible decompression bombs. For most ML, pixel size requirements are well below the limit imposed by PIL so we are ok with that limit as a heuristic to protect us.
Our current option is to use pdf2image which converts pdfs to images and specify a pixel size (e.g. width=1700 pixels, height=2200 pixels) there but I was curious if this can be done at the point of loading an image.
I would like to compress and image using PIL, but when I execute it the image is still the same size. How do I solve it?
What I tried so far?
img.save('Compressed_image.tiff', dpi=[300,300], quality=35)
I tried to change the quality but the file size is always the same.
define the new width and height of the image
then use the following to downscale, before saving
img = img.resize( (width, height), Image.LANCZOS)
also, since TIFF is a lossless format, reducing the quality parameter would not have any effect on the saved filesize.
I used PIL to open and save the same jpg image, but the size reduces significantly. Could somebody explained what's going on under the hood?
I run
a = Image.open('a.jpg')
a.save('b.jpg')
a.jpg has the size 5MB, whereas b.jpg is only 600KB. and I enlarge them and compared side by side and basically see no differences in the picture quality. Could somebody explain this?
Much appreciated!
The default save quality for jpg in Pillow is 75. I bet your original image is saved with a higher quality setting.
The image quality, on a scale from 0 (worst) to 95 (best), or the string keep. The default is 75. Values above 95 should be avoided; 100 disables portions of the JPEG compression algorithm, and results in large files with hardly any gain in image quality. The value keep is only valid for JPEG files and will retain the original image quality level, subsampling, and qtables.
From https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html#jpeg
I am currently working in Steganography Project and I am a beginner.
I developed the following code in Python to complement the Last bit of all pixels and save the Resultant Image as New Image say: Output.jpg
Everything in the code works fine until I save the image using img.save() function: when I reopen the same image the pixels Remains unchanged.
I am aiming to use Java for this project.
from PIL import Image
img=Image.open("P:\Input.jpg")
img=img.convert("RGB")
width,height=img.size
pix=img.load()
for i in range(width):
for j in range(height):
r,g,b=pix[i,j]
bin_b=bin(b)
bin_list=list(bin_b)
if bin_list[-1] == 0:
bin_list[-1]=1
else:
bin_list[-1]=0
b=int("".join(str(i) for i in bin_list),2)
pix[i,j]=(r,g,b)
img.save("P:\Sampleout.jpg")
I need to get modified pixels as either oldpixels+1 or oldpixels-1 and not same oldpixel in position i,j
One possible problem is that you're using jpeg format. This image format is, by default, compressed using a lossy compression scheme that is allowed to alter slightly values of the pixel data to get a smaller footprint for the image. There is no guarantee that the lowest bit (or any bit actually) will be the same after saving to jpeg and reloading.
If you want to experiment on this kind of processing you should use lossless formats like BMP, TGA or PNG instead. JPEG also has a lossless mode, but it's not used by default by most software.
I want to reduce the file size of a PNG file using Python. I have gone through a lot of material on the internet, but I could not find anything where I would reduce the file size for an image without changing the dimensions i.e. height/width. What I have found is how to change the dimensions of the image, using PIL or some other library of Python.
How can I reduce image file size while keeping it's dimensions constant?
PNG is a lossless format but it still can be compressed in a lossless fashion. Pillow's Image class comes with a png writer accepting a compress_level parameter.
It can easily be demonstrated that it works:
Step 1: Load generic rgb lena image in .png format:
import os
import requests
from PIL import Image
from io import BytesIO
img_url = 'http://pngnq.sourceforge.net/testimages/lena.png'
response = requests.get(img_url)
img = Image.open(BytesIO(response.content))
Step 2: Write png with compress_level=0:
path_uncompressed = './lena_uncompressed.png'
img.save(path_uncompressed,compress_level=0)
print(os.path.getsize(path_uncompressed))
> 691968
Step 3: Write png with compress_level=9:
path_compressed = './lena_compressed.png'
img.save(path_compressed,compress_level=9)
print(os.path.getsize(path_compressed))
> 406889
which in this case gives us a respectable 30% compression without any obvious image quality degradation (which should be expected for a lossless compression algorithm).
PNG is lossless format and obviously it will consume more space.
If you are only concerned on resolution, then you can convert to any of the lossy form like JPG.
https://whatis.techtarget.com/definition/lossless-and-lossy-compression
The dimension after conversion would be the same, but quality depends on the compression needed
Snippet to convert PNG to JPG
from PIL import Image
im = Image.open("Picture2.png")
rgb_im = im.convert('RGB')
rgb_im.save('Picture2.jpg')
By default, most PNG writers will use the maximum compression setting, so trying to change that will not help much. Uncompressed PNGs exist, but they make no sense, I don't think you'll run into many of those.
Thus, the only way of making PNGs significantly smaller is to reduce the number of pixels it stores, or to reduce the number of colors it stores. You specifically said not to want to reduce the number of pixels, so the other option is to reduce the number of colors.
Most PNG files will be in "true color" mode (typically 24 bits per pixel, with one byte each for the red, green and blue components of each pixel). However, it is also possible to make indexed PNG files. These store a color map (a.k.a. palette), and a single value per pixel, the index into a color map. If you, for example, pick a color map of 64 entries, then each pixel will need 6 bits to encode the index. You'd store 64*3 bytes + 3/4 bytes per pixel (which of course compress as well). I found this web site comparing a few example images, what they'd look like and how big the file ends up being when reducing colors.
This other question shows how to use PIL to convert an RGB image to an indexed image:
img.convert("P", palette=Image.ADAPTIVE)
This seems to generate an 8-bit color map though, PIL has no support for smaller color maps. The PyPNG module would allow you to write PNG files with any number of colors in the color map.