Initial commit

.gitattributes

@@ -0,0 +1,2 @@
+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

@@ -0,0 +1,160 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

@@ -1,2 +1,32 @@
-# vs-gmfss_fortuna
-GMFSS_Fortuna function for VapourSynth
+# GMFSS_Fortuna
+The All-In-One GMFSS: Dedicated for Anime Video Frame Interpolation, based on https://github.com/98mxr/GMFSS_Fortuna.
+
+
+## Dependencies
+- [CuPy](https://docs.cupy.dev/en/stable/install.html)
+- [NumPy](https://numpy.org/install)
+- [PyTorch](https://pytorch.org/get-started) 1.13.1
+- [VapourSynth](http://www.vapoursynth.com/) R55+
+
+`trt` requires additional runtime libraries:
+- [CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit) 11.7
+- [cuDNN](https://developer.nvidia.com/cudnn) 8.6
+- [TensorRT](https://developer.nvidia.com/tensorrt) 8.6.0.12
+
+For ease of installation on Windows, you can download the 7z file on [Releases](https://github.com/HolyWu/vs-gmfss_fortuna/releases) which contains required runtime libraries and Python wheel file. Unzip the file to the location that you chose. Add `<unzippath>/bin` to your system `PATH`. Additionally, add `<unzippath>` to `CUDA_PATH` environment variable because CuPy relies on it. Finally pip install the Python wheel file.
+
+
+## Installation
+```
+pip install -U vsgmfss-fortuna
+```
+
+
+## Usage
+```python
+from vsgmfss_fortuna import gmfss_fortuna
+
+ret = gmfss_fortuna(clip)
+```
+
+See `__init__.py` for the description of the parameters.

pyproject.toml

@@ -0,0 +1,31 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "vsgmfss_fortuna"
+version = "1.0.0"
+description = "GMFSS_Fortuna function for VapourSynth"
+readme = "README.md"
+requires-python = ">=3.10"
+license = {file = "LICENSE"}
+authors = [{name = "HolyWu", email = "[email protected]"}]
+keywords = ["GMFSS_Fortuna", "VapourSynth"]
+classifiers = [
+  "License :: OSI Approved :: MIT License",
+  "Operating System :: OS Independent",
+  "Programming Language :: Python :: 3.10",
+  "Topic :: Multimedia :: Video"
+]
+dependencies = [
+  "cupy-cuda11x>=12.0.0",
+  "numpy>=1.24.2",
+  "tensorrt>=8.6.0",
+  "torch>=1.13.1",
+  "torch-tensorrt-fx-only>=1.4.0.dev0",
+  "VapourSynth>=55"
+]
+
+[project.urls]
+"Homepage" = "https://github.com/HolyWu/vs-gmfss_fortuna"
+"Bug Tracker" = "https://github.com/HolyWu/vs-gmfss_fortuna/issues"

vsgmfss_fortuna/FeatureNet.py

@@ -0,0 +1,34 @@
+import torch.nn as nn
+
+from .util import MyPReLU
+
+
+class FeatureNet(nn.Module):
+    """The quadratic model"""
+    def __init__(self):
+        super(FeatureNet, self).__init__()
+        self.block1 = nn.Sequential(
+            MyPReLU(),
+            nn.Conv2d(3, 64, 3, 2, 1),
+            MyPReLU(),
+            nn.Conv2d(64, 64, 3, 1, 1),
+        )
+        self.block2 = nn.Sequential(
+            MyPReLU(),
+            nn.Conv2d(64, 128, 3, 2, 1),
+            MyPReLU(),
+            nn.Conv2d(128, 128, 3, 1, 1),
+        )
+        self.block3 = nn.Sequential(
+            MyPReLU(),
+            nn.Conv2d(128, 192, 3, 2, 1),
+            MyPReLU(),
+            nn.Conv2d(192, 192, 3, 1, 1),
+        )
+
+    def forward(self, x):
+        x1 = self.block1(x)
+        x2 = self.block2(x1)
+        x3 = self.block3(x2)
+
+        return x1, x2, x3