bfiocpp 0.4.0

Tensorstore Based Backend for BFIO

This is the new backend for bfio, using Tensorstore and other high-throughput IO library

Build Requirements

bfiocpp uses Tensorstore for reading and writing OME Tiff and OME Zarr files. So Tensorstore build requirements are needed to be satisfied for bfiocpp also. For Linux, these are the requirements:

• GCC 10 or later
• Clang 8 or later
• Python 3.8 or later
• CMake 3.24 or later
• Perl, for building libaom from source (default). Must be in PATH. Not required if -DTENSORSTORE_USE_SYSTEM_LIBAOM=ON is specified.
• NASM, for building libjpeg-turbo, libaom, and dav1d from source (default). Must be in PATH.Not required if -DTENSORSTORE_USE_SYSTEM_{JPEG,LIBAOM,DAV1D}=ON is specified.
• GNU Patch or equivalent. Must be in PATH.

Since Tensorstore requires MACOSX_DEPLOYMENT_TARGET to be 10.14 or higher (to support sized/aligned operator new/delete.), bfiocpp needs the same.

Building and Installing

Here is an example of building and installing bfiocpp in a Python virtual environment.

python -m venv build_venv
source build_venv/bin/activate
git clone https://github.com/PolusAI/bfiocpp.git 
cd bfiocpp
mkdir build_deps
cd build_deps
../ci-utils/install_prereq_linux.sh
cd ..
export BFIOCPP_DEP_DIR=./build_deps/local_install
python setup.py install -vv