Yome2x - Photo Enhance vs. ImageX - AI Photo Enhancer Utilizzo e statistiche

- ImageX built-in a variety of latest image enhancement AI algorithms. - AI Super Resolution, enlarges the image, improve the image quality, noise reduction. - AI Frame Interpolation, improve the smoothness of animated image. - Dozens of pre-trained models, suitable for different styles. - Local offline processing, no upload required, ensuring privacy. - Support GPU hardware acceleration, faster processing speed. - Rich format, support JPG PNG APNG GIF WebP HEIC format. - No ads. - Supports iOS and Mac (sold separately). (For batch processing and faster speeds, we recommend the Mac version) Privacy Protection: All images are processed offline locally on the device, no uploading, no privacy risk. Non-Pro version restrictions: - iOS 1. Any side of the output that is higher than 1280 pixels or the output that is an animated image does not support saving and sharing. 2. Batch saving and sharing are not supported. - Mac 1. Any side of the output that is higher than 1280 pixels or the output that is an animated image will be ignored. Subscription: 1. Upgrade to Pro with Subscription or Lifetime Purchase to unlock full access. 2. If subscribing to the Pro version (monthly subscription or annual subscription; lifetime purchases are not included), the subscription will automatically renew unless you cancel the subscription 24 hours before the end of the next recurring date. 3. Pro for iOS and Mac are sold separately; iOS in-app purchases are only applicable to iOS App use, and Mac in-app purchases are only applicable to Mac App use. 4. For batch processing and faster speeds, please choose the Mac version. Privacy Policy: https://www.tinyperfectapps.com/res/imagex/policy/imagex_privacy_policy.html Terms of Use: https://www.tinyperfectapps.com/res/imagex/policy/imagex_terms_and_conditions.html Reference projects: Waifu2x - nagadomi/waifu2x: https://github.com/nagadomi/waifu2x (MIT) - lltcggie/waifu2x-caffe: https://github.com/lltcggie/waifu2x-caffe (MIT) - nihui/waifu2x-ncnn-vulkan: https://github.com/nihui/waifu2x-ncnn-vulkan (MIT) Real-CUGAN - bilibili/ailab: https://github.com/bilibili/ailab/tree/main/Real-CUGAN (MIT) - nihui/realcugan-ncnn-vulkan: https://github.com/nihui/realcugan-ncnn-vulkan (MIT) Real-ESRGAN - xinntao/Real-ESRGAN: https://github.com/xinntao/Real-ESRGAN (BSD3) - xinntao/Real-ESRGAN-ncnn-vulkan: https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan (MIT) SRMD - cszn/SRMD: https://github.com/cszn/SRMD (MIT) - cszn/KAIR: https://github.com/cszn/KAIR (MIT) - nihui/srmd-ncnn-vulkan: https://github.com/nihui/srmd-ncnn-vulkan (MIT) RealSR - jixiaozhong/RealSR: https://github.com/jixiaozhong/RealSR (Apache2) - nihui/realsr-ncnn-vulkan: https://github.com/nihui/realsr-ncnn-vulkan (MIT) RIFE - megvii-research/ECCV2022-RIFE: https://github.com/megvii-research/ECCV2022-RIFE (MIT) - nihui/rife-ncnn-vulkan: https://github.com/nihui/rife-ncnn-vulkan (MIT) IFRNet - ltkong218/IFRNet: https://github.com/ltkong218/IFRNet (MIT) - nihui/ifrnet-ncnn-vulkan: https://github.com/nihui/ifrnet-ncnn-vulkan (MIT)