Since opencv-python version 4.3.0.*, manylinux1 wheels were replaced by manylinux2014 wheels. If your pip is too old, it will try to use the new source distribution introduced in 4.3.0.38 to manually build OpenCV because it does not know how to install manylinux2014 wheels. However, source build will also fail because of too old pip because it does not understand build dependencies in pyproject.toml. To use the new manylinux2014 pre-built wheels (or to build from source), your pip version must be >= 19.3. Please upgrade pip with pip install --upgrade pip.
A: It's easier for users to understand opencv-python than cv2 and it makes it easier to find the package with search engines. cv2 (old interface in old OpenCV versions was named as cv) is the name that OpenCV developers chose when they created the binding generators. This is kept as the import name to be consistent with different kind of tutorials around the internet. Changing the import name or behaviour would be also confusing to experienced users who are accustomed to the import cv2.
I'm using the opencv crate which has many c++ bindings. Every time I try to compile a tiny adjustment, the Building step takes around 35-40secs for an 18 line program. Every time. Is there anything I can do to bring this down?
Hi, I am trying to develop an App using SwiftUI together with OpenCV framework. After I built the app, the ContentView has a warning to import opencv2. the warning is ":'/Users/kinsuenlau/Downloads/opencv2.framework/Modules/opencv2.swiftmodule/Project/x86_64-apple-ios-simulator.swiftsourceinfo' is either malformed or generated by a different Swift version. Note that it uses an unstable format and may leak internal project details, it should not be distributed alongside modules"
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The targeted build detail I got from manually inspecting the .swiftinterface file in the downloaded "iOS pack" (XCFramework) - specifically ./Versions/A/Modules/opencv2.swiftmodule/x86_64-apple-ios-simulator.swiftinterface, which starts with the following:
Digging around in Google a bit, I found this gist that details someone else wanting to basically do this process, which you might find useful: Make opencv2.xcframework for iOS arm64, and iOSSimulator arm64 & x86_64 GitHub
Since 2012, support for OpenCV was taken over by a non-profit foundation named OpenCV.org, which maintains a developer site and a user website. You can get the official releases from SourceForge or take the latest sources from the opencv GitHub.
PyImageJ: a Python wrapper for ImageJ2 enabling access to all of ImageJ2 and the original ImageJ from Python. Together with opencv-python, the two programs can be used together with NumPy arrays as a common data structure.
Notice : GOTURN being a CNN based tracker, uses a Caffe model for tracking. The Caffe model and the proto text file must be present in the directory in which the code is present. These files can also be downloaded from the opencv_extra repository, concatenated, and extracted before use.
DNN example shows how to use Intel RealSense cameras with existing Deep Neural Network algorithms. The demo is derived from MobileNet Single-Shot Detector example provided with opencv. We modify it to work with Intel RealSense cameras and take advantage of depth data (in a very basic way).
The demo will load existing Caffe model (see another tutorial here) and use it to classify objects within the RGB image. Once object is detected, the demo will calculate approximate distance to the object using the depth data: