Showing 4 open source projects for "c graphics libraries"

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  • 1
    Video Object Remover – Frame-Accurate

    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.

    Video Object Remover – Frame Accurate Edition is a free and open-source desktop application that helps you remove unwanted objects, logos, or watermarks from videos using brush-based masking and AI inpainting. 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...
    Downloads: 32 This Week
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  • 2
    Warlock-Studio

    Warlock-Studio

    AI Suite for upscaling, interpolating & restoring images/videos

    v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system...
    Downloads: 21 This Week
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  • 3
    Upscale

    Upscale

    This program is upscaling any image by a factor 2 using an algorithm

    This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV.
    Downloads: 0 This Week
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  • 4
    Super-résolution via CNN

    Super-résolution via CNN

    Super resolution using a CNN, based on the work of the DGtal team

    Super-resolution using a CNN, based on the work of the DGtal team. First of all, an Nvidia graphics card (neither AMD nor Intel integrated) is highly recommended to parallelize the CNN. You will then need to install CUDA. No CUDA = dozens of times slower. This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test...
    Downloads: 0 This Week
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