OpenCV 4.5.0 軟體資訊交流 Mac

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OpenCV 4.5.0 Mac


Keka 是一個有用和易於使用的 Mac OS X 壓縮和備份應用程序,用於管理桌面或 Finder 窗口中壓縮文件的所有方面。通過多種文件壓縮功能,支持各種主流壓縮格式,拖放界面,Keka 絕對值得在您的 Dock 或者主窗口上找到一席之地。為了讓 Keka 對新手和專業人士更具吸引力,這個 100%免費的應用程序在壓縮和提取歸檔格式方面具有廣泛的兼容性,但是您必須意識到並非所有的提取格式也都支持壓縮。除了 ZIP,RAR 和 7 -Zip 等流行格式外,Keka for Mac 還可以管理 ISO 格式的流行 CD / DVD 光盤鏡像文件,這對於希望利用 CD / DVD 虛擬驅動器.

提取文件是 100%無縫的,直接集成了桌面,Dock 和 Finder。所有主要格式的檔案都可以通過簡單的雙擊或拖放到 Dock 或主窗口上的 Keka 圖標上進行操作和提取。有了這樣的易用性,您可以選擇 Keka 作為主要的歸檔操作實用程序.

Keka 文件歸檔程序可以免費安裝,在 Mac OS 10.5 或更新的版本上沒有任何限制(舊的舊版本仍然可以使用在 Mac OS X 10.4 Tiger 上)。應用程序不具有訂閱,單次購買,解鎖或任何應用程序內功能,並沒有應用程序內的廣告。這個應用程序的開發人員只接受捐款,保持這個項目活著,並跟踪接收許多未來的更新.

壓縮格式支持:
7z,Zip,焦油,Gzip,Bzip2,DMG 和 ISO.

支持的提取格式:
RAR,7z,Lzma,Zip ,Tar,Gzip,Bzip2,ISO,EXE,CAB,PAX 以及更多.

檔案版本 OpenCV 4.5.0
檔案名稱 opencv-4.5.0-ios-framework.zip
檔案大小
系統 Mac OS X 10.7 or later
軟體類型 免費軟體
作者 aONe
更新日期 http://www.kekaosx.com/
軟體類型 2020-10-12
更新日誌

What's new in this version:

- OpenCV 4.5.0 licence has been changed to Apache 2: OE-32 - Change OpenCV License to Apache 2
- OpenJPEG replaces Jasper in distributed Windows packages: #18194
- Added support for OpenCL multiple contexts

DNN module:
Improved layers / activations / supported more models:
- ONNX: ReduceSum, Gather, improved Reshape

Intel® Inference Engine backend ( OpenVINO™ ):
- added support for OpenVINO 2021.1 release

- Fixes and optimizations in DNN CUDA backend (thanks to @YashasSamaga): PRs

G-API module:
- Added Python bindings for the general G-API (#17493), inference and streaming support are currently in progress
- Introduced serialization API, currently limited. A graph can be serialized to a byte stream (std::vector) and then reconstructed back to a cv::GComputation object
- OpenVINO NN backend has been moved to the latest OpenVINO "Core" APIs
- Now it is easier to declare a graph with a dynamic number of inputs or outputs (GIn() / GOut() support operator+=)
- Added "mask", extended "convertTo" with 16S, also added performance tests on Core kernels for the Fluid backend
- Added standard NN post-processing operations like parseYolo and parseSSD to turn NN results into a structured graph-based data format (e.g. GArray)

Added value initialization for GArray so now one can write:
- cv::GArray arr = std::vector { 1, 2, 3 }
- to associate a cv::GArray<> with a value at graph construction stage
- cv::GMat bitwise operators are extended with a cv::GScalar operand
- Introduced a new graph data type cv::GFrame and its data storage type cv::MediaFrame to start handling media-oriented formats (like NV12 or YUV images with external memory) in the graph

And many other great contributions from OpenCV community:
- flann module fixes / improvements by @pemmanuelviel: PRs
- Add Robot-World/Hand-Eye calibration function

GSoC 2020 merged projects:
- GSoC: Better SIFT in the main repository
- GSoC: Improvement of Random Sample Consensus in OpenCV
- GSoC: Real-time Single Object Tracking using Deep Learning
- GSoC: Revise/improve Text and Digit Recognition Samples
- GSoC: Optimize OpenCV for RISC-V
- GSoC (opencv_contrib): OpenCV bindings for Julia
- GSoC (opencv_contrib): Implement Macbeth Chart detector and AprilTag3
- GSoC (opencv_contrib): Depth Fusion for large scale environments

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