Showing 7 open source projects for "input-output model"

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  • 1
    Real-ESRGAN GUI

    Real-ESRGAN GUI

    Cross-platform GUI for image upscaler Real-ESRGAN

    ...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 pack arm64single-architecture applications by themselves. Real-ESRGAN can only enlarge the input image with a fixed 2-4x magnification (related to the selected model). This functionality is achieved by downsampling using a conventional scaling algorithm after multiple calls to Real-ESRGAN. Split each frame of the GIF and record the duration, zoom in one by one and then merge. Drag an image file or directory to any position in the window, and its path can be automatically set as the input.
    Downloads: 145 This Week
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  • 2
    Segmentation Models

    Segmentation Models

    Segmentation models with pretrained backbones. PyTorch

    ...Preparing your data the same way as during weights pre-training may give you better results (higher metric score and faster convergence). It is not necessary in case you train the whole model, not only the decoder. Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported. Input channels parameter allows you to create models, which process tensors with an arbitrary number of channels.
    Downloads: 0 This Week
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  • 3
    MLT Multimedia Framework
    A multimedia authoring and processing framework and a video playout server for television broadcasting.
    Downloads: 7 This Week
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  • 4
    VSGAN

    VSGAN

    VapourSynth Single Image Super-Resolution Generative Adversarial

    Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS) inputs. ...
    Downloads: 1 This Week
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  • 5
    Render32

    Render32

    Command-line video compositing and audio mixing tools

    Render is a program for creating composite BMP image sequences. These images are composited as specified in a text configuration file. Mixer is a program for mixing film soundtracks. It accepts input files in WAV format and outputs a mixed soundtrack in WAV format. Each input channel can contain one or more audio files that are edited and mixed using a cue sheet. The maximum number of channels is a compile-time parameter.
    Downloads: 0 This Week
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  • 6
    Super-résolution via CNN

    Super-résolution via CNN

    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 batch and lrto the learning rate. Low res images should be located in a "dataset/input" folder, and high res targets in a "dataset/target" folder, where each different quality image has the same name in both folders.
    Downloads: 0 This Week
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  • 7
    This is a MATLAB model of an end-to-end chain compliant to the DVB-T2 standard (ETSI EN 302 755 available from www.etsi.org). It was originally developed within the DVB consortium (www.dvb.org) by AICIA, BBC, Pace, Panasonic and SIDSA.
    Downloads: 6 This Week
    Last Update:
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