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SVG++ | OpenCV | |
---|---|---|
2 | 196 | |
521 | 75,423 | |
- | 1.4% | |
5.4 | 9.9 | |
about 2 months ago | 6 days ago | |
C++ | C++ | |
Boost Software License 1.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SVG++
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Realtime rasterization of vector graphics
Maybe SVG++, if you're looking for an industrial-grade solution?
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Plain Text. With Lines
Congratulations, now you replaced a trivial file format that (from a quick glance at the code) needed about ~35 of easily readable and self-contained Lua code to parse with an external dependency that would be much larger and harder to follow and either having (at least) an XML parser as its own dependency or implementing its own XML parsing, as well as being at the mercy of their developers. Also unless you are using some highly popular library, you may end up with some abandoned dependency.
Examples of both are at [0] (C++ based parser, you'd also need to write some bindings for lua) and [1] (Lua based parser for a subset of the format, abandoned for almost a decade).
There are times when using an external dependency might be a good idea, but a text-based file format that describes lines and can be implemented in a few lines of code is not one.
[0] https://github.com/svgpp/svgpp
[1] https://github.com/luapower/svg_parser
OpenCV
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การจำแนกสายพันธุ์มะม่วง โดยใช้ Visual Geometry Group 16 (VGG16) ใน Python
Referenceshttps https://www.kaggle.com/datasets/riyaelizashaju/skin-disease-image-dataset-balanced?fbclid=IwAR3wbTp8l5yo_5fx6HAX8Vd2-9cca3khAc8EiBGFObaALfdVid29IuB_rYE https://keras.io/api/applications/vgg/ https://www.tensorflow.org/tutorials/images/cnn?hl=th https://opencv.org/
- Opencv-Python adds support for Pathlike objects
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
- OpenCV calls for help
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Image segmentation in huggingface
You'll need to plot the predictions. There are a few open source tools to do that, supervision is one you can use (https://github.com/roboflow/supervision) and opencv is another common option (https://github.com/opencv/opencv)
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Looking for a Windows auto-clicker with conditions
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/).
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NodeJS: Blurring Human Faces in Photos
The OpenCV4NodeJs A.I. library provides an interface for calling OpenCV routines in NodeJS.
- NodeJS - Ofuscando rostos humanos em fotos
- SIMD Everywhere Optimization from ARM Neon to RISC-V Vector Extensions
- VidCutter: A program for lossless video cutting
What are some alternatives?
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
libvips - A fast image processing library with low memory needs.
VTK - Mirror of Visualization Toolkit repository
CxImage
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
OpenImageIO - Reading, writing, and processing images in a wide variety of file formats, using a format-agnostic API, aimed at VFX applications.
CImg - The CImg Library is a small and open-source C++ toolkit for image processing
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
ULIS - Utility Library for Imaging Systems
Boost.GIL - Boost.GIL - Generic Image Library | Requires C++14 since Boost 1.80