Showing 41 open source projects for "batch image processor"

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  • 1
    video-subtitle-remover

    video-subtitle-remover

    AI-based tool for removing hardsubs and text-like watermarks

    Video-subtitle-remover (VSR) is an AI-based software that removes hardcoded subtitles from videos or Pictures.
    Downloads: 33 This Week
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  • 2
    Super-PDF-Editor

    Super-PDF-Editor

    World's most comprehensive, powerful, process-based PDF editor

    World's most comprehensive, powerful, process-based and lighting fast PDF reader, editor and batch processor. PDF editing with 60+ features rich tools and function like OCR pdf and images and produce output like searchable PDF, Text, Hocr, Box, Unlv. Also, improve image enhancement before OCR operation for better OCR performance. pdf Imposition, etc. Super PDF Editor is best for bulk pdf processing, especially for the printing industry.
    Downloads: 11 This Week
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  • 3
    Super-PDF-Editor-Lite

    Super-PDF-Editor-Lite

    World's most comprehensive, powerful, process-based PDF editor

    World's most comprehensive, powerful, process-based and lighting fast PDF reader, editor and batch processor. Includes features like Create PDF from Images, HTML, Text files. Create a processing log file. Extract Page, Split Page, Rotate Page, Merge Page, Duplicate page, Move Page, Printing, and Compress Page. Improve image enhancement before OCR operation for better OCR performance. pdf Imposition, etc. Super PDF Editor is best for bulk pdf processing, especially for the printing industry. ...
    Downloads: 3 This Week
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  • 4
    FrankMocap

    FrankMocap

    A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator

    FrankMocap is a monocular 3D human capture system that estimates body, hand, and optionally face pose from a single RGB image or video. It regresses parametric human models (e.g., SMPL/SMPL-X) directly, producing temporally stable meshes and joint angles suitable for animation or analytics. The pipeline couples a robust 2D keypoint detector with 3D mesh regression networks and priors that keep results anatomically plausible. It can run frame-by-frame or with temporal smoothing, and includes demo apps for live webcam capture as well as batch processing. ...
    Downloads: 0 This Week
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  • 5
    Disco Diffusion

    Disco Diffusion

    Notebooks, models and techniques for the generation of AI Art

    ...Initial QoL improvements added, including user-friendly UI, settings+prompt saving, and improved google drive folder organization. Now includes sizing options, intermediate saves and fixed image prompts and Perlin inits. the unexposed batch option since it doesn't work.
    Downloads: 1 This Week
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  • 6
    StudioGAN

    StudioGAN

    StudioGAN is a Pytorch library providing implementations of networks

    StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea. Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT,...
    Downloads: 0 This Week
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  • 7
    DnCNN

    DnCNN

    Beyond a Gaussian Denoiser: Residual Learning of Deep CNN

    This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image...
    Downloads: 5 This Week
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  • 8
    Detectron2

    Detectron2

    Next-generation platform for object detection and segmentation

    Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll...
    Downloads: 1 This Week
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  • 9
    SimSiam

    SimSiam

    PyTorch implementation of SimSiam

    SimSiam is a PyTorch implementation of “Exploring Simple Siamese Representation Learning” by Xinlei Chen and Kaiming He. The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing...
    Downloads: 4 This Week
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  • 10
    BerryNet

    BerryNet

    Deep learning gateway on Raspberry Pi and other edge devices

    This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events...
    Downloads: 0 This Week
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  • 11
    FixRes

    FixRes

    Reproduces results of "Fixing the train-test resolution discrepancy"

    ...FixRes demonstrates that a mismatch between training and testing resolutions often leads to suboptimal accuracy, and fine-tuning the classifier and batch normalization layers at higher test resolutions significantly enhances performance. The repository includes pretrained models, feature embeddings, and evaluation scripts corresponding to the experiments reported in the NeurIPS 2019 paper “Fixing the train-test resolution discrepancy.”
    Downloads: 3 This Week
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  • 12
    DIGITS

    DIGITS

    Deep Learning GPU training system

    The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting...
    Downloads: 0 This Week
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  • 13
    IMAGINE

    IMAGINE

    Biological image viewer and processor

    Detection, enumeration, and sizing of biological organisms by image analysis.
    Downloads: 0 This Week
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  • 14

    LBP in multiple platforms

    LBP implementation in multiple computing platforms (ARM,GPU, DSP...)

    ...This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014
    Downloads: 0 This Week
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  • 15
    Tifftool is a high-performance tool to clean scanned documents in preparation for onscreen display or for OCR. Features include skew correction, orientation correction, despeckle, page alignment, split pages and batch processing.
    Downloads: 0 This Week
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  • 16
    This projects aim is to create an easy to use system for computer perception and computer vision tasks. It consists of three parts; a computer perception library (libCP), a processor based framework, and a graphical userinterface.
    Downloads: 0 This Week
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