diff --git a/README.rst b/README.rst index 3c08e55..0b2fcb0 100644 --- a/README.rst +++ b/README.rst @@ -33,6 +33,22 @@ If you have Python installed, you can install ChipStream from PyPI pip install chipstream[cli,gui] +Since version 0.6.0, you can also make use of torch-based segmentation +models. + +:: + + pip install chipstream[cli,gui,torch] + +If you have a CUDA-compatible GPU and your Python installation cannot access the +GPU (`torch.cuda.is_available()` is `False`), installing torch via the pytorch +index URL might help: + +:: + + pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121 + + Execution --------- If you have installed ChipStream from PyPI, you can start it with diff --git a/build-recipes/win_ChipStream.spec b/build-recipes/win_ChipStream.spec index 5b6e39f..80ee379 100644 --- a/build-recipes/win_ChipStream.spec +++ b/build-recipes/win_ChipStream.spec @@ -60,7 +60,7 @@ gui_exe = EXE( strip=False, upx=False, icon=NAME + ".ico", - console=bool(chipstream.__version__.count("post"))) + console=bool(chipstream.__version__.count("post") or chipstream.__version__.count("a"))) coll = COLLECT( cli_exe,