# EMCFsys pinned Windows runtime environment
#
# This file records the package versions used for the released napari plugin
# and the MMLab-backend examples in demo_notebook.ipynb.
#
# Reference platform
#   OS: Windows 11、 Windows 10、 Linux Ubuntu 22.04
#   Python: 3.11.10
#   GPU: NVIDIA GeForce RTX 3090, CUDA runtime used by PyTorch: 11.8
#   
#
# Recommended clean installation
#   conda create -n EMCF_napari python=3.11.10 -y
#   conda activate EMCF_napari
#   python -m pip install ninja==1.13.0
#   python -m pip install --no-build-isolation -r pined_requirement.txt
#   python -m pip install -e .

# OpenMMLab backend
# see in demo_notebook.ipynb for the usage of the OpenMMLab backend
# Please follow the instructions in the OpenMMLab documentation to install the OpenMMLab backend and its dependencies.

# openmim==0.3.9
# mmcv==2.2.0
# mmengine==0.10.7
# mmsegmentation==1.2.2
# mmdetection==3.3.0
# mmdet==3.3.0
# addict==2.4.0
# model-index==0.1.11
# prettytable==3.17.0
# terminaltables==3.1.10
# yapf==0.43.0
# ninja==1.13.0


# Foundation-model and deep-learning utilities
timm==1.0.22
transformers==5.12.1
tokenizers==0.22.2
safetensors==0.6.2
huggingface-hub==1.21.0
einops==0.8.1
ftfy==6.3.1
thop==0.1.1.post2209072238

# Numerical, image-processing, and evaluation packages
numpy==2.2.6
scipy==1.16.3
scikit-image==0.25.2
scikit-learn==1.9.0
opencv-python==4.12.0.88
pandas==2.3.3
pillow==12.0.0
matplotlib==3.10.7
seaborn==0.13.2
albumentations==2.0.8
albucore==0.0.24
imageio==2.37.2
tifffile==2025.10.16
pycocotools==2.0.11
shapely==2.1.2
lmdb==1.7.5
tqdm==4.65.2
PyYAML==6.0.3

# Annotation and dataset-conversion packages
labelme==5.9.1
imgviz==1.7.6

# Image evaluation
pytorch_fid==0.3.0
sahi==0.12.6
fire==0.7.1

# hash
pywavelets==1.9.0

# Napari GUI
# napari[all]