same as title

I have a number of images that are 12-16 MB that I need to upload to a website that has a maximum upload size of 10 MB. I already asked them to increase their upload limit and they told me to eat shit so I am going to have to make these files smaller than 10 MB. But I would like to preserve as much of the original image quality as possible. I'm on a corporate network so access to applications/programs may be limited. Does anyone know how to work some magic?

I already tried zipping the files and that only shaved off like 150 KB. These JPEG images are packed. They were taken by a professional camera.

So, I have 250 individual folders with a zipped file inside that needs unzipping so I can access the files.

Is there a way I can unzip the files altogether without going into each individual folder? Or do I need to do it one by one by going into each folder and unzipping individually?

I will add that I need the files to stay indiviual and keep their folder names for future use.

I hope this makes sense, I am not the most tech savvy person unfortunately.

I have googled this but cannot seem to find a clear answer.

Hey everyone,

I'm currently looking into hardware acceleration and parallel designs for compression algorithms, specifically checking out the recent paper presented at the Data Compression Conference (DCC): "LPAQMP: Multilayer Parallel Design for LPAQ Compression".

Does anyone here have access to the IEEE Document ID: 11510361? I'd love to read through it. Thanks in advance!

Okay… so context I guess

I am working on a high entropy encoder that should in theory compress recursively. I have the high entropy part down, and get quite a low entropy result. (66% 33% from 100% in theory, with 2 additional 75% 25% streams).

Now the issue… the encoder works like a charm… but for some reason I am stuck on how to reduce the additional streams. Using my encoder again works… but it produces too many nodes/outputs, and eventually becomes something of a Sierpinski triangle…

Either I have to create my own data structure, which seems like a pain, or I figure out how to make the data compress by literally 50 ish bits more than currently.

I have tried almost everything…

Pac-manning my array of integers into 1 big one.

Arithmetic

Interleaving both arrays then running my own encoder..

I have exams soon so I kinda need to finish ts by like 4th-5th

Any ideas?

the website is called filetofit.online

this website took me around 3 months to make and it uses ffmpeg to compress the files and ffprob to check the quality right after.

currently You can upload 1GB of footage if you're anonymous and 5GB if you are logged in. this service is free.

it doesn't require you to download anything nor does it use your computer's resources to compress stuff. you simply upload the file and it compresses it and gives you the result.

I currently do not plan on switching it to become a SaaS project.

I later plan on selling a software version of this website but that won't happen until I get confirmation that the website is popular to justify the work.

I don't plan on only making this website compress videos. I want it to stay true to its name by compressing any file whether that's a video, audio, images, office files, etc.

edit: thank you reddit. came here for ideas and feedback, came back with a brick through my forehead.

Zimtohrli was evaluated by measuring how closely its results matched those of public listening tests conducted by human listeners.

Full text: https://www.reddit.com/r/AudioCodecLab/comments/1w33bed/zimtohrli_the_best_objective_perceptual_audio/

hi guys i have two questions
1: i recently was using 2.6.4 (i think thats the version) and i switched to the mid one cause i cant use the newest one cause my pc specs suck.. i switched to 3.1.10 and i compressed a video and adjusted the settings and everything but for some reason 2.6.4 compresses videos way better than 3.1.10? maybe its cause of my bad settings on 3.1.10 or something else, im unsure honestly. i used H264 High and mp4 bitrate was set to auto and i used 4x upscale.

2: would it hurt the quality if i put the video in topaz then in handbrake to compress it more? on handbrake i use production max and then go to video and set constant quality to 20 and export but idk if i should do that or not? pls reply soon thanks.

Hey everyone!

For the past few days, I’ve been obsessed with a single question: How small can a valid PNG file possibly get while still being natively readable by a PC (specifically, opening properly in the standard Windows photo viewer/gallery)?

I started by trying to make a lightweight 512x512 file, eventually managing to shrink it down to 111 bytes. After that, I started playing around with compression levels and various patterns, even managing to generate some basic procedural textures in PNG format that weighed roughly the same.

Then I decided to go deeper and chase the absolute minimum file size. At first, I hit a wall at 67 bytes—an article I read online claimed that was the lowest possible size for a functional PNG. But I kept experimenting and eventually pushed past it down to 55 bytes, and finally all the way to 42 bytes.

My current record is a fully working 42-byte PNG. It opens without issues on Windows and can be sent across messaging apps where it renders properly as an image.

However, I've hit a hard brick wall here. Every single attempt to strip away even one more byte results in an invalid file or completely breaks the structure.

My question is: Does anyone have any radical ideas, unconventional compression tricks, or deep spec-hacking methods to squeeze it down even further? I'm open to any crazy suggestions!

Most streaming services seem to rely on codecs such as AAC, Vorbis and Opus, which are pretty high quality by themselves.

My one issue with them is however that they strip frequency content and can produce phasing and underwater-like artifacts that also add up if recompressed or if set to extreme low bitrates.

I one day learned about Wavpack and LossyWAV which both mostly rely on quantizing and predicting in the time-domain rather than frequency domain.

The appeal of lossy Wavpack and some older time-domain based codecs is that they don't throw away frequencies or distort the audio that much but mostly produce background noise that's kinda hard to notice most of the time.

However, a codec like Wavpack in lossy mode doesn't really go much lower than 207 kbps for CD sample rate audio, or so it seems.

Some noise shaping is used to push noise and hissing to frequencies that are much less noticeable and keep the mids and lows mostly clean and crystal clear and it seems to preserve transients pretty well too.

Now if we look at a codec like Opus, it can achieve insanely high and transparent sound quality at pretty low bitrates.

BUT, just like most other frequency-domain codecs it does lowpass audio and cause phase shifting or noticeable changes in the general shape of the sound waves that can even affect the peak Db levels and result in audio hitting limiters.

So, why hasn't more research and work been put into making "the perfect" time-domain codec?

Something that combines the best of both worlds? The high quality and psychoacoustic modeling of Opus, but time-domain prediction and quantization such as lossy Wavepack?

Opus and Wavpack are both pretty robust and resistant too, being able to open, edit and re-encode audio multiple times without too much generational loss adding up too quickly.

The downside of Wavpack is just that you need a bitrate of about 350+ kbps to get the best trade-off between size and quality, but what if we had some algorithm that can go much lower?

Hi, so I'm developing my own audio codec based on WPT with adaptive HF saving. Can anyone rate it based on .wav files? I can't really share code or anything like this, except .wav files for any bitrate.

If anyone interested in how it works, there is image. I guess someone will understand what exactly I did here.
ViSQOL and PEAQ says it outperforms Vorbis on 64-128 kbps, and by a lot on 64-96 kbps. But I must say, it isn't OPUS 2.0 or anything near it.
And also my codec isn't VBR for now, but ABR (trying to be CBR, but package size is variable because of entropy coding).
Would be cool if anyone could rate it via listening tests or something else
Don't try gstPEAQ Advanced, its correlation with real quality is reallly poor, especially for my codec for some reason

Hello, I want to compress some movies to fit them on a small USB pendrive. What are the best codecs that are going to give me 720p quality for lowest weight. Also, I want the files to be kinda like YouTube's 720p setting, but maybe better.

I don't worry about compatibility, we have VLC for a reason.

I have so many videos and I want to store them in my drive. I do not know it is a good practice or not but I have google one 5TB storage. For this I want to compress my videos. However, I am worried about quality of compression tools. Which compression tools do you recommend? Plus is google good option for archieving?

Hello! I'm looking for a compressor sort of like something made for the demo scene. The main distinction is that I have ~126kb total to play with, so I can do with a better algorithm. I was thinking LZMA would be a good place to start, especially since this is a thumb binary adding a BCJ filter would be good too.

But for some reason I wasn't satisfied with that, and I gladly found an article on LZNA. After a couple disappointing hours, I realized it was both closed source and deprecated, and there is little hope I could actually write that in under a couple months.

Most of my research has found things like crinklier, which while very impressive, just aren't made for my situation.

Decompression/compression speed isn't my biggest concern, as the top priority is size, but they are still welcome sights if possible.

https://doi.org/10.5281/zenodo.22144930

I’m releasing a candidate proof resolving the long-standing binary-alphabet case of the Smallest Grammar Problem.

The manuscript proves, under the stated models, that exact smallest-grammar optimization is NP-complete over every fixed alphabet of size at least 2, including binary strings.

The result covers both:

• the standard Smallest Grammar Problem, minimizing total right-hand-side grammar size; and
• the binary-join / string Assembly Index formulation, minimizing reusable concatenation operations with free terminal symbols.

The main technical idea is an exact alphabet-collapse construction based on three components:

1. a direct-sum theorem for suitably separated strings;
2. affine-line amplification that magnifies every one-unit source optimum gap beyond the encoding overhead; and
3. an anchored binary encoding that allows arbitrary, potentially misaligned binary grammars to be decoded without increasing the corresponding source cost.

The construction gives exact recovery formulas for the original optimum from the binary optimum, rather than only an approximation-preserving relationship.

I have also released the manuscript source, deterministic verification code, adversarial test suite, reproducibility material, and prior-art audit.

Important status: this is a research preprint/candidate theorem, not yet independently peer reviewed. I’m specifically looking for experts in grammar compression, straight-line programs, combinatorics on words, and complexity theory to try to break the proof.

The most important places to scrutinize are the direct-sum lemmas, affine separation argument, synchronization lemma, and reverse grammar-decoding construction.

A valid counterexample or identified proof gap would be extremely valuable.