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#Conda install opencv python 3.5 64 Bit#
I use Windows 7 64 bit for now if that matters.
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I would like to know if there is a more sensible way to handle this. So, I am planning to do a clean install from scratch. I tried conda install opencv directly, but it does not work for me since I am using Python 3.5 which is higher version that default OpenCV library in. I had conflicting libraries, path issues and all sorts of weird problems. After doing a simple pip install opencv-python or pip install opencv-contrib-python and trying to import the library, I ran into this issue: python Python 3.5.2 Anaconda 4.2.0 (64-bit) (default, Jul 5 2016, 11:41:13) MSC v.1900 64 b. I had to switch between versions when required. I am aiming to use Jupyter notebook and Spyder as the IDE. Install necessary libraries: pip install opencv-python3.4.2.17 pip install opencv-contrib-python3.4.2.17 Windows: 1. Colorize means to apply a colormap to an image.
#Conda install opencv python 3.5 how to#
Python 2.7, with pip: pip install cmapy Python 3.x, with pip: pip3 install cmapy Or, in a Conda environment: conda install -c conda-forge cmapy How to use Colorize images. But loads of libraries are still 2.7 which means I need both. OpenCV > 3.3.0 (to use cv2.appl圜olorMap()). I tried conda install opencv conda install cv2 I also tried searching conda search cv No cigar. Similarly, I prefer to use Python 3.5 as that is the future and the way things go. Create condo environment¶ conda create -n explainableAI python3.5 source activate explainableAI conda install tensorflow conda install keras conda install jupyter. I'm trying to install OpenCV for Python through Anaconda, but I can't seem to figure this out. I prefer to use the 64 bit version for better RAM use and efficiency butģ2bit version is needed as well because some libraries are 32bit. I would like to use Python for scientific applications and after some research decided that I will use Anaconda as it comes bundled with loads of packages and add new modules using conda install through the cmd is easy.