Got real tired of juggling five tabs and a terminal to compress different file types. So I built something that handles them ALL in one place.Supports 50+ input formats. If something is compressible it will handle it. Upload a file, it figures out what it is, compresses it, hands it back. Ephemeral storage for 2 hours. Format conversion works pretty well too.The part I'm most happy with is the...
I'm excited to introduce intern.work, a dedicated job board and learning hub created solely for internships.
While looking for interns to join my company, I realized there are very, very few places for internships alone so I decided to create on myself. I also noticed that most regular platforms emphasize big-ticket positions, such as "Remote Software Engineers", but overlook a crucial stepping stone for many in their career which are internships.
Why intern.work?
1. By dedicating a platform exclusively for internships, I aim to ensure that both companies and interns find exactly what they're looking for without the noise of other job types. 2. Not just a job board, but a holistic hub (hopefully) that guides prospective interns on making the most of their internships, from preparing for interviews to maximizing their time at the position. 3. Community Driven: A space for interns to share experiences, seek advice, and connect with potential mentors or peers in the industry (coming soon)
I would love to get feedback and feature suggestions.
Visit intern.work for more.
Hello HN,A few days back we launched SupaRes which is an image restoration/enhancement platform. What I think is unique about that product is that it offers not only general single-image super-resolution but also a few other enhancements such as automatic white-balance, denoising, tone improvement, or low-light boost.We have some customers in our regular business [1] who requested something...
If you want to stick with the old-school PNG icons, we open-sourced `icopack` - our internal tool for efficient packing of individual PNGs into a highly-optimised ICO files [2].
[1] https://optidash.ai/blog/optimizing-favicons-for-the-worlds-...
It's a perceptually lossless optimization and recompression.
We use saliency detection (trained on an eye-tracker) which tells us where the human vision system would look in the images and optimise those fragments (heatmaps) using our own comparison metrics.
If you're interested in the details shoot me an email to przemek [at] optidash [dot] ai
[1]: https://optidash.ai/blog/optimizing-images-on-the-worlds-top...
A few days ago I've lanunched Optidash - ML-enhanced image optimization and processing API. Optidash builds on top of another product of mine (Pixaven) and runs entirely on Mac Pros (as pioneered by imgix).
While Optidash supports all major image formats for optimization and processing, I am mainly focused on JPEGs. All open-source JPEG optimizers share pretty much the same algo - create N copies of master image at different quality settings and, using various metrics (ssim/dssim/psnr), pick the variant with the "best" quality to size ratio.
Optidash takes a different approach. We use saliency detection to identify the most important area(s) of a master image. That basically tell us how the human eye would see the image and where it would look most likely. Once the saliency heatmap is computed, we crop that fragment and pass it to our Core ML model trained to predict optimal encoding settings. That approach also comes with a performance benefit - only the most salient areas are passed to the model (far less pixel data to process) and it also ensures we don't saturate pretty limited GPU memory we have available on Mac Pros (we use 2nd gen so D700, 6GB VRAM).
Estimating output Q value is one thing but we are also training additional models to help us determine optimal quantization table for a given salient region.
As I am still evaluating the above approach and general API design, I'd love to get some feedback.
Yesterday I launched a simple, yet very effective tool for online face detection, cropping and filtering. The idea is very simple - upload as many images as you like and FaceMaze will give you back all the faces cropped from those input images. You can control padding, border radius and output image format.
FaceMaze rides on top of Pixaven's [1] infrastructure and, at its very core, uses Apple's Vison framework to do all the heavy lifting. The accuracy of this is not as flawless as for example Tencent's DSFD that will give you back even face reflections on flat surfaces but it's really good enough for everyday usage.
I am not aware of any other free and unlimited web interfaces for face detection hence the title of this Show HN post.
[1]: https://www.pixaven.com [2]: https://github.com/TencentYoutuResearch/FaceDetection-DSFD
The foundation of any image processing pipeline on MacOS/iOS is Image IO that offers crazy fast codecs for over a dozen different image formats. Even though I had to write extra integrations for WebP and animated GIFs it was really worth the effort. Native HEIC/HEIF support (reading and writing) is also neat.
Apple's CoreML is another piece of software I am using more and more at Pixaven. The ease of testing and deployment of new ML models is just amazing (and yes, I am learning a lot along the way).
With Metal Performance Shaders we have absolute control over pixels and direct access to the underlying hardware. For us that means we can rapidly test and deploy new CoreML models and also the ability to quickly respond to any feature-request.
Pixaven is a service meant (ideally) for businesses running at scale. If you're a large e-commerce platform with literally millions of new images (and their variants) created per day you would be looking for a solid platform to process this visual content for you.