Codesofinterest.com Website Review

For a while now, the most reliable two ways to get TensorFlow installed is to either use the pip package, or compile from source. Compiling TensorFlow from source takes hours, and still prone to errors (see Failed Attempts at Building TensorFlow GPU from Source But not anymore. Because the conda native TensorFlow packages are here now. NOTE: Dont install the pip and conda versions of TensorFlow on the same conda environment. If you already have the pip version installed As you know, OpenCV is capable of reading from any connected camera in your system, whether its a built-in we*cam (in a laptop) or a USB But what if, you wanted to read from more than one cam at the same time? Don't forget to subscribe! Fun and exciting De*p Learning experiments, Computer Vision, and Tech noticed that its starting to take up a lot of disk space (sometimes tens of GBs). One reason is that anaconda environments are completely isolated workspaces from each other with their own copy of Python. So, the more environments you have, the larger the space needed by anaconda. But the other reason is that anaconda keeps a cache of the package files, tarba*ls etc. of the packages youve installed. This is great when you need to reinstall the same packages. But, over time, the space can add So, how do we clean up this cache and regain some disk space? For the last 3 weeks, Ive been trying to build TensorFlow from source. I wanted to get TensorFlow GPU version working on Windows with CUDA 9.2 and cuDNN 7.1. Since the pre-built wheels only work with CUDA 9.0, the only way we can get it working with 9.2 is to build it The Windows build of TensorFlow is done using CMake. The official instructions are here: Unfortunately, as I found out after multiple attempts, the build process is not as simple as it sounds. But, I decided to post the steps I took - which didnt work - so that you all may be able use it as a reference if you decided to try it out First, I started with gathering all the dependencies to build on Windows 10: