Open Source Computer Vision Library
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Updated
Mar 8, 2022 - C++
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Digital image processing is the use of algorithms to make computers analyze the content of digital images.
Open Source Computer Vision Library
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Content aware image cropping
JavaScript image cropper.
Content aware image resize library
Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)
An Android transformation library providing a variety of image transformations for Glide.
The friendly PIL fork (Python Imaging Library)
Best Practices, code samples, and documentation for Computer Vision.
Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!
CVPR 2022 论文和开源项目合集
As reported by deepsource in here we abuse from using built-in input function in our functionality.
We target to have a clean and healthy source code free of risk.
Replace variable names whether it makes sense e.g. for image based functionality input -> image ; in l
Fast and secure standalone server for resizing and converting remote images
OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
A follow up on SixLabors/ImageSharp#1378 (comment).
Currently 32 bit test execution is only done for .NET Framework, with dotnet xunit which is an obsolete tool today, we need to adapt dotnet test, and add 32 bit CI targets for both net5.0 and netcoreapp3.1. Opening an issue to remember and track this debt.
Blurry is an easy blur library for Android
Segmentation models with pretrained backbones. PyTorch.
a language for fast, portable data-parallel computation
This is a feature request for a utility function for cropping images from a bounding box.
Note this need comes up a lot, particularly for 2D images - see this discussion on image.sc for an example, including prototype code. It would be nice to have a full nD solution though. Possibly something that
Go package for computer vision using OpenCV 4 and beyond.
Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.
HUBTo explore the structure of a dataset it is convenient to have nicer and more informative prints of dataset objects and samples
now
> ds
Dataset(path='hub://activeloop/abalone_full_dataset', tensors=['length', 'diameter', 'height', 'weight'])A view controller for iOS that allows users to crop portions of UIImage objects
Enhancement
A discussion in #614 revealed a good place for improvement - we should ensure that input image is continuous upon start of the augmentation pipeline. This could be implemented by adding
image = np.ascontiguousarray(image)to image and mask targets.A proposed place to add this call - somewhere at the beginning of
A.Compose.__call__.