ImageX

About This Build

ImageX is listed on IPA Search as an iOS app in the utilities category. This page shows it as updated Aug 26, 2023, credits Lyu Jiahao as the developer, indexes the current IPA from RipeStore. Note : Features behind in-app purchases. • AI Super Resolution • AI Frame Interpolation • Dozens of models • Local processing • GPU acceleration • Rich formats • Waifu2x •.

Before sideloading, verify that the listed build matches your device and install method. The package size is 280.1 MB, the listed minimum requirement is iOS 15.0+. The bundle identifier is com.tinyperfectapps.imagex, which is useful when comparing this build with releases from other repositories or checking whether a future update targets the same app.

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Some repositories publish only a very short app summary, so the version, source, compatibility notes, and screenshots on this page may be the most reliable details available before installation.

Description

Note : Features behind in-app purchases. • AI Super Resolution • AI Frame Interpolation • Dozens of models • Local processing • GPU acceleration • Rich formats • Waifu2x • Real-CUGAN • Real-ESRGAN • SRMD • RealSR • RIFE • IFRNet - 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)

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