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test pipeline choosing least blurry image out of every 120 frames for smaller datasets #mused
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fail w/medium dataset from 360 video (~6,000 images) like small, but full requires too much memory, next strategy is render each input separately #mused
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clean data & filter blurry images then start processing/aligning image datasets again #mused
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do training with better input images #avatarai
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Reduce image quality #curated
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make minimum data available for micro level pixels on #hoodmaps lower to show more data for smaller cities (for @adriaanvanrossum)
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fix memory bug #interiorai by scaling input image smaller
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#pintura further refine image size and crop input
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try save money by reducing steps of upscaler from 18 to 9 and image gen from 40 to 30 without noticeable differences so then we save 1 minute of GPU time per image gen or $0.07 per photo or tens of thousands $ per month #photoai
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load videos low res #skrrt
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change image to higher res images
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better image processing failure fallbacks in #readbot
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if #hoodmaps not enough data in high detail, use low detail data and make it 3d instead
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maybe use a smaller screenshot frame #openform
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fix blurry background getting upscaled again #photoai
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resize slow loading images #codewithhugo
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try 768x768 training instead of 512x512 #photoai
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reduced image compression to improve quality of images on gocapture #meratek
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test & fail 3d environment reconstruction from only 50 images instead of video #mused
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#contracting Cut preview images down to 600px instead of 300px because it’s no longer 2017 and we now have higher res screens and more bandwidth and the old preview images were looking blurru
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