Search Results for "jd-gui"
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Showing 8 open source projects for "jd-gui"
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Real-ESRGAN GUI
Cross-platform GUI for image upscaler Real-ESRGAN
The graphic interface of Real-ESRGAN, a practical and beautiful image magnification tool, refers to the design of waifu2x-caffe. This program is a graphical interface of Real-ESRGAN's command line program Real-ESRGAN-ncnn-vulkan , written in Python and tkinter, and supports Windows, Ubuntu and macOS platforms. According to actual measurements, arm64the single-architecture performance is better than universal2the dual- architecture Mac on the Apple chip, so Apple chip users are advised to... -
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Video2X
A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K
A lossless video/GIF/image upscale achieved with waifu2x, Anime4K, SRMD and RealSR. Started in Hack the Valley 2, 2018. The latest Windows update is built based on version 4.8.1. GUI is not available for 5.0.0 yet, but is already under development. Go to the GUI page to see the basic usage of the GUI. Try the mirror if you can't download releases directly from GitHub. You can use Video2X on Google Colab for free if you don't have a powerful GPU of your own. You can borrow a powerful GPU (Tesla K80, T4, P4, or P100) on Google's server for free for a maximum of 12 hours per session. ... -
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LosslessCut
The swiss army knife of lossless video/audio editing
LosslessCut aims to be the ultimate cross platform FFmpeg GUI for extremely fast and lossless operations on video, audio, subtitle and other related media files. The main feature is lossless trimming and cutting of video and audio files, which is great for saving space by rough-cutting your large video files taken from a video camera, GoPro, drone, etc. It lets you quickly extract the good parts from your videos and discard many gigabytes of data without doing a slow re-encode and thereby losing quality. ... -
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Video Object Remover – Frame-Accurate
🎥 A free & open-source Python tool to remove unwanted objects from videos frame-by-frame using brush masking and AI inpainting (OpenCV + FFmpeg). EXE included.
...The tool extracts video frames using FFmpeg, lets you mask objects frame-by-frame, and removes them using OpenCV. Built with Python and Tkinter, it features a modern dark-themed GUI, adjustable brush tool, zoom control, and real-time logging. The cleaned video is rebuilt and exported with original quality. Includes a precompiled Windows EXE for normal users (no Python required) and full source code for developers or students. Perfect for YouTubers, video editors, educators, and open-source enthusiasts. 🖥️ Website: https://projectworlds.in 📺 YouTube: https://youtube.com/@projectworlds 📬 Support: https://projectworlds.in/contact-us -
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5
enhancr
Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT
enhancr is an elegant and easy to use GUI for Video Frame Interpolation and Video Upscaling which takes advantage of artificial intelligence - built using node.js and Electron. It was created to enhance the user experience for anyone interested in enhancing video footage using artificial intelligence. The GUI was designed to provide a stunning experience powered by state-of-the-art technologies without feeling clunky and outdated like other alternatives. -
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AI Models
A repository of trained models
...The GUI is one of the best looking applications out there and is personally my go to option. While yes builds are paid, it is well worth your money and beats any other GUI out there currently. -
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Easy Upscale
A simple image upscaler application using EDSR, ESPCN, FSRCNN, etc.
...The concept of the application is an application to upgrade/enhance image quality. The main theme is queues, we implement circular queues for pooling/storing a list of images to be upscaled. Gui creation is made manually using the tkinter library. For the upscale process itself, it uses the OpenCV library with a model obtained from open source. Checked using vermin. Minimum required versions: 3.6 Incompatible versions: 2. -
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MNIST-WGAN
A C# WGAN
...The sources and features of the project can be found in the wiki. Before use, one should verify that the network architecture is as-desired. This may be done with the GUI to the right of the number display. The "Default" button resets the network to hard-coded values which I have verified function. The "Reset" button sets the ACTIVE network to whatever architecture is displayed. In order to change which network is displayed, use the "Critic [1] or Generator [0]" checkbox. To begin training the network, press the "Train" button, after which you may use the "Clear" button to reset the average error and average percent correct value textboxes. ...
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