ImageX - AI Photo Enhancer 1.1.3

嘉豪吕 – Freeware – iOS
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ImageX incorporates a range of cutting-edge AI algorithms for image enhancement. It offers features such as AI Super Resolution, which enlarges images and improves their quality while reducing noise. Additionally, AI Frame Interpolation enhances the smoothness of animated images. The software includes dozens of pre-trained models suitable for different styles.
One standout feature is the ability to process images locally offline, eliminating the need for uploads and ensuring privacy. The software also supports GPU hardware acceleration, resulting in faster processing speeds. ImageX supports a variety of formats including JPG, PNG, APNG, GIF, WebP, and HEIC.
Notably, the software does not include any ads. It is compatible with iOS and Mac systems, although they are sold separately. For batch processing and faster speeds, it is recommended to use the Mac version.
Privacy protection is a priority with ImageX. All image processing occurs offline on the user's device, with no uploading involved, thus eliminating any privacy risks.
The non-Pro version of ImageX has certain restrictions:
<ul>
 <li>In the iOS version, saving and sharing are not supported for outputs with a height exceeding 1280 pixels or animated images. Additionally, batch saving and sharing are not available.</li>
 <li>In the Mac version, outputs with a height exceeding 1280 pixels or animated images will be ignored.</li>
</ul>
To unlock full access to ImageX's features, users can upgrade to the Pro version through a subscription or lifetime purchase. If subscribing to the Pro version (monthly or annually), automatic renewal occurs unless canceled 24 hours prior to the next recurring date. It's important to note that Pro versions for iOS and Mac are sold separately, with iOS in-app purchases applicable only to iOS App usage and Mac in-app purchases applicable only to Mac App usage.
ImageX's privacy policy and terms of use can be found at the following links:
<ul>
 <li>Privacy Policy: <a href="https://www.tinyperfectapps.com/res/imagex/policy/imagex_privacy_policy.html">https://www.tinyperfectapps.com/res/imagex/policy/imagex_privacy_policy.html</a></li>
 <li>Terms of Use: <a href="https://www.tinyperfectapps.com/res/imagex/policy/imagex_terms_and_conditions.html">https://www.tinyperfectapps.com/res/imagex/policy/imagex_terms_and_conditions.html</a></li>
</ul>
ImageX has been developed based on various reference projects such as Waifu2x, Real-CUGAN, Real-ESRGAN, SRMD, RealSR, RIFE, IFRNet. These projects have been released under licenses including MIT, BSD3, and Apache2. Below are the links to their respective repositories:
<ul>
 <li>Waifu2x:
 <ul>
 <li>nagadomi/waifu2x: <a href="https://github.com/nagadomi/waifu2x">https://github.com/nagadomi/waifu2x</a> (MIT)</li>
 <li>lltcggie/waifu2x-caffe: <a href="https://github.com/lltcggie/waifu2x-caffe">https://github.com/lltcggie/waifu2x-caffe</a> (MIT)</li>
 <li>nihui/waifu2x-ncnn-vulkan: <a href="https://github.com/nihui/waifu2x-ncnn-vulkan">https://github.com/nihui/waifu2x-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>Real-CUGAN:
 <ul>
 <li>bilibili/ailab: <a href="https://github.com/bilibili/ailab/tree/main/Real-CUGAN">https://github.com/bilibili/ailab/tree/main/Real-CUGAN</a> (MIT)</li>
 <li>nihui/realcugan-ncnn-vulkan: <a href="https://github.com/nihui/realcugan-ncnn-vulkan">https://github.com/nihui/realcugan-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>Real-ESRGAN:
 <ul>
 <li>xinntao/Real-ESRGAN: <a href="https://github.com/xinntao/Real-ESRGAN">https://github.com/xinntao/Real-ESRGAN</a> (BSD3)</li>
 <li>xinntao/Real-ESRGAN-ncnn-vulkan: <a href="https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan">https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>SRMD:
 <ul>
 <li>cszn/SRMD: <a href="https://github.com/cszn/SRMD">https://github.com/cszn/SRMD</a> (MIT)</li>
 <li>cszn/KAIR: <a href="https://github.com/cszn/KAIR">https://github.com/cszn/KAIR</a> (MIT)</li>
 <li>nihui/srmd-ncnn-vulkan: <a href="https://github.com/nihui/srmd-ncnn-vulkan">https://github.com/nihui/srmd-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>RealSR:
 <ul>
 <li>jixiaozhong/RealSR: <a href="https://github.com/jixiaozhong/RealSR">https://github.com/jixiaozhong/RealSR</a> (Apache2)</li>
 <li>nihui/realsr-ncnn-vulkan: <a href="https://github.com/nihui/realsr-ncnn-vulkan">https://github.com/nihui/realsr-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>RIFE:
 <ul>
 <li>megvii-research/ECCV2022-RIFE: <a href="https://github.com/megvii-research/ECCV2022-RIFE">https://github.com/megvii-research/ECCV2022-RIFE</a> (MIT)</li>
 <li>nihui/rife-ncnn-vulkan: <a href="https://github.com/nihui/rife-ncnn-vulkan">https://github.com/nihui/rife-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
 <li>IFRNet:
 <ul>
 <li>ltkong218/IFRNet: <a href="https://github.com/ltkong218/IFRNet">https://github.com/ltkong218/IFRNet</a> (MIT)</li>
 <li>nihui/ifrnet-ncnn-vulkan: <a href="https://github.com/nihui/ifrnet-ncnn-vulkan">https://github.com/nihui/ifrnet-ncnn-vulkan</a> (MIT)</li>
 </ul>
 </li>
</ul>

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