The Deep-Shot Converter is used to combine photos with a wide shooting angle and such with deep zoom, into single images with an exponential pixel grid. It combines, increasing one picture’s impact and at the same time saves lots of memory, as the files mainly consist out of carefully arranged compressed colour value. As most of today’s photographs will never be printed, their digital features get more important. There is basically two types of images, raster-based images following rows and columns and vector images, based on coloured lines and forms. Deep-Shots combine the advantages of both by using an exponentially growing net structure. This makes end-users able to create incredibly deep pictures without consuming high amounts of computing power. Pictures can be zoomed up to 10’000+ times. As you can imagine, this isn’t possible for raster-based images such as PNG. The project started in October 2021 with some simple sketches on sticky notes. In the same year a patent application was written and a first prototype was designed. Today’s version now offers the option to include as many photos as wanted and the project is still evolving. There are many opportunities. For example a launch into camera software seems possible, especially super-zoom-cameras could gain great effort. The adjustment of the zoom as well as the shooting of the photographs can be automated, the results can immediately be merged into a simultaneously arising net structure.
Based on our record, Autotracer.org seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Autotracer.org. Aut is my go to for dead simple vectors. Source: almost 2 years ago
Save your font image as a png or jpg and run it through https://autotracer.org. Source: over 2 years ago
You can run this through https://autotracer.org as well if you need that svg-ness. Source: over 2 years ago
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