Out-of-date reports cause misinterpreted insights.
Poor data quality sabotages new AI models. Inconsistent data could lead to high integration costs. And every year, the volume of data collected grows at staggering rates.īut harnessing value from this data has proved challenging for most. Obviously it isn't going to make any meaningful difference in a 6x4" print.Ībsolutely - at the end of the day only you can decide how much you use it, and whether it's a worthwhile tool for you.Businesses have been collecting and storing massive amounts of data from apps, services, Internet of Things (IoT) sensors, and other sources for decades. The results with Topaz Gigapixel AI would generally print quite a bit better at larger sizes. My suspicion is that few amateurs/hobbyists need this sort of thing, but if it makes someone happy to have this in their toolbox, then they should definitely buy one!įunnily enough 2x is exactly how I do use it. Would I pay extra for a special enlarging tool? Probably not, I don't enlarge images enough to make it worth my while. If a 2X enlarged image will look good, then likely, the unenlarged image would too with the same display requirements. Personally, I don't think a 2X enlargement is all that good a test, which is what most people test at. It's hard to predict what enlarging will do with any tool. The imperfect nature of the added pixels coupled with sharpening can add artefacts sometimes. Sharpening is frequently done at the end to reenforce the lines between areas of color and luminance. Well, not really, enlarging algorithms try to figure out how to ADD pixels to make the photo physically larger.
IMO its just a more sophisticated way of sharpening that adds alot of artefacts and makes file sized unnecesarily big. I find the results to be not much better than conventional sharpneing.
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