Solving the Missing CalcEMD2 Function in OpenCV3 for Anaconda Python
Solving the Missing CalcEMD2 Function in OpenCV3 for Anaconda Python
If you’re a data scientist working with the Anaconda Python distribution and OpenCV3, you may have encountered a peculiar issue: the absence of the CalcEMD2 function. This function is crucial for many image processing tasks, but it’s mysteriously missing from the OpenCV3 module in Anaconda Python. In this blog post, we’ll explore how to solve this problem and get your image processing tasks back on track.
Understanding the Issue
The Earth Mover’s Distance (EMD), also known as the Wasserstein distance, is a measure of the distance between two probability distributions. It’s a powerful tool in image processing and computer vision tasks, such as texture comparison and object recognition.
In OpenCV, the function CalcEMD2 is used to compute the EMD. However, if you’re using the OpenCV3 module in Anaconda Python, you may have noticed that this function is missing. This can be a significant roadblock for data scientists who rely on this function for their work.
Why is CalcEMD2 Missing?
The root of the problem lies in the way OpenCV3 is compiled and packaged for the Anaconda Python distribution. The CalcEMD2 function is part of the cv2.cv submodule, which is not included in the OpenCV3 module for Anaconda Python.
This omission is not a bug, but a deliberate decision made by the maintainers of the OpenCV package for Anaconda. The cv2.cv submodule is considered legacy code, and its functions have been moved to other submodules in newer versions of OpenCV. However, CalcEMD2 was not moved to a new submodule, and as a result, it’s missing from OpenCV3 in Anaconda Python.
The Solution: Building OpenCV from Source
The good news is that there’s a solution to this problem: building OpenCV from source. This process allows you to include the cv2.cv submodule and access the CalcEMD2 function.
Here’s a step-by-step guide:
Download the OpenCV source code: You can download the source code from the OpenCV GitHub repository. Make sure to download the 3.x version that matches the version of OpenCV you’re using in Anaconda Python.
Install the necessary build tools: You’ll need CMake and a C++ compiler to build OpenCV from source. You can install these tools using the Anaconda package manager:
conda install -c anaconda cmake
conda install -c anaconda gcc
- Build OpenCV: Navigate to the directory where you downloaded the OpenCV source code and create a new directory for the build files:
cd opencv-3.x
mkdir build
cd build
Then, run CMake to configure the build:
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
Finally, compile OpenCV:
make -j$(nproc)
- Install OpenCV: After the build process is complete, you can install OpenCV:
sudo make install
Now, you should be able to import the cv2.cv submodule and use the CalcEMD2 function in Anaconda Python.
Conclusion
While it’s unfortunate that the CalcEMD2 function is missing from the OpenCV3 module in Anaconda Python, the issue can be resolved by building OpenCV from source. This process may seem daunting if you’re not familiar with it, but it’s a valuable skill to have as a data scientist. With this knowledge, you can customize your tools to fit your needs and overcome obstacles in your work.
Remember, the world of data science is constantly evolving, and sometimes, the tools we use don’t evolve in the way we need them to. In these cases, it’s up to us to adapt and find solutions. Happy coding!
Keywords: OpenCV3, Anaconda Python, CalcEMD2, Earth Mover’s Distance, Image Processing, Data Science, Build from Source, cv2.cv, CMake, GCC
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