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Browser image resize, better than highest PIL quality

Preamble
I'm displaying an image from a Django back-end into a 26 x 26px sized (css) <img> tag.
I can do this two ways:
Resize on the back-end (Pillow) to 26x26 (cropping to keep the aspect ratio)
Send the full size image and let CSS do the sizing
Issue
Using the LANCZOS algorithm for resizing and saving the result as 100% quality Jpg, the displayed image looks so much worse than the one resized by the browser.
Why is that, and is there any way to fix it?
EDIT: Testing on a Retina display
EDIT: Bicubic looks very similar to Lanczos

This article here [1] says that Retina displays (high-DPI displays) are going to try to display 2x more pixels in the same area. Area that is also measured in pixels, the pixels you actually declare in CSS.
So this is where my confusion came from. The solution was to generate the thumbnails twice the size being displayed.

In my experience, PIL/Pillow (hereafter simply “Pillow”) can behave very differently with small images than it does with large ones – not just in its resizing operations but generally – but so you might as well test out all of the methods Pillow offers, e.g.:
# q.v. https://gist.github.com/fish2000/d85befaf289c664b6a9f44d1b56e57da#file-asscat-py-L129-L134
from PIL import Image
# q.v. PIL.Image constants of the same (yet uppercased) names:
interpolation_methods = frozenset({
"box",
"bilinear", "bicubic",
"hamming", "lanczos",
"nearest" })
def interpol(name):
""" Return a PIL/Pillow image interpolation method constant by name """
return getattr(Image, name.upper())
size = (26, 26)
avatar = Image.open(…) # load your source avatar image
methods = (interpol(method) for method in interpolation_methods)
scaled = (avatar.resize(size, resample=method) for method in methods)
# you can save these out for more granular inspection:
previews = list(scaled)
for preview in previews:
preview.show()
… keep in mind that Image.NEAREST can yield surprisingly decent results for small sizes – that, and the fact that Pillow is not in any way Adobe® Photoshop™, and as such can’t really be tasked with replicating results you may have gotten out of same.
But so, w/r/t whether or not to scale using CSS (or any other client-based method): it’s always better to send less bytes over the wire, if possible – but that doesn’t mean it can’t be done. I’m a perfectionist, personally, but if pressed for time or money I am not pedantic about it.

How can i properly resize my images for further processing?

I want to resize my images( to a smaller size) :
How can I resize my images properly without the bad pixels effect for further cnn processing afterward.

Your problems are due to interpolation artifacts. As you can check in the documentation for cv2.resize, by default BILINEAR is used. You should probably go with their suggestion and try using the INTER_AREA version. You may also want to check other options and see which one suits you best.

You need to look at vector images here at Wikipedia if you really want a clear picture in a small size. OpenCV library doesn't provide a function for converting bitmap images to vector images.

OpenCV how to replace cut out object with background

I have two images, one image which contains a box and one without. There is a small vertical disparity between the two pictures since the camera was not at the same spot and was translated a bit. I want to cut out the box and replace the hole with the information from the other picture.
I want to achieve something like this (a slide from a computer vision course)
I thought about using the cv2.createBackgroundSubtractorMOG2() method, but it does not seem to work with only 2 pictures.
Simply subtracting the picture from another does not work either because of the disparity.
The course suggests using RANSAC to compute the most likely relationship between two pictures and subtract the area thaht changed a lot. But how do I actually fill in the holes?
Many thanks in advance!!

If you plant ot use only a pair of images (or only a few images), image stitching methods are better than background subtraction.
The steps are:
Calculate homography between the two images.
Warp the second image to overlap the second.
Replace the region with the human with pixels from the warped image.
This link shows a basic example of image stitching. You will need extra work if both images have humans in different places, but otherwise it should not be hard to tweak this code.

You can try this library for background subtraction issues. https://github.com/andrewssobral/bgslibrary
there is python wrappers of this tool.

Image resize to a specific height and width in django python

I have a django based website in which I have created profiles of people working in the organisation. Since this is a redesign effort, I used the already existing profile pictures. The size of current profile image style is 170x190px. Since the images already exist and are of different sizes, I want to crop them to the size specified above. But how do I decide from which side I have to crop?
Currently, I have applied style of 170by190 to all the images while displaying in profiles, but most of them look distorted as the aspect ratios do not match.
I have tried PIL thumbnail function but it does not fit the need.
Please suggest a solution.

Well, you have to resize pictures, but images ratio create huge impact on final result. As images have some ratio, and you cannot simply resize them to 170px190px without prior adjusting of their ratio, so you have to update( not crop them!) images before resizing them to get best possible output, it can be done in next ways:
Crop them manually to desired ratio (17:19). (take a while if you have plenty of images)
Create script which add padding to that images if image ratio is close to required, all images which ratio is far away from desired mark as 'human cropping required' and work with their ratio later by own (semi-manual, so still may be really time consuming)
Spend some time and write face recognation function, then process images with that function and find faces, then crop them from origin image, but before: add padding to achieve desired radio (17:19) at top and bottom of face. (recommended)
Some links which may be use full for you:
Face Recognition With Python, in Under 25 Lines of Code
facereclib module, they probably are able to help you.
Image Manipulation, The Hitchhiker’s Guide
Good luck !

Use sorl-thumbnail, you don't need to crop every image manually.

Rendering image independent of size?

I'm currently working on a small game using pygame.
Right now I render images the standard way, by loading them and then blitting them to my main surface. This is great, if I want to work with an individual image size. Yet, I'd like to take in any NxN image and use it at an MxM resolution. Is there a technique for this that doesn't use surfarray and numeric? Something that already exists in pygame? If not, do you think it would be expensive to compute this?
I'd like to stretch the image. So, upscale or downscale the image. Sorry I wasn't clearer.

There is no single command to do this. You will first have to change the size using pygame.transform.scale, then make a rect of the same size, and set its place, and finally blit. It would probably be wisest to do this in a definition.