
Show HN: Optidash – ML-enhanced image optimization API - matylla
https://optidash.ai
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matylla
Hello folks,

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.

