diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..32030ff
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,209 @@
+### Linux ###
+*~
+
+# temporary files which can be created if a process still has a handle open of a deleted file
+.fuse_hidden*
+
+# KDE directory preferences
+.directory
+
+# Linux trash folder which might appear on any partition or disk
+.Trash-*
+
+# .nfs files are created when an open file is removed but is still being accessed
+.nfs*
+
+### OSX ###
+# General
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must end with two \r
+Icon
+
+
+# Thumbnails
+._*
+
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk
+
+### Python ###
+# 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
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__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/
+
+### Windows ###
+# Windows thumbnail cache files
+Thumbs.db
+Thumbs.db:encryptable
+ehthumbs.db
+ehthumbs_vista.db
+
+# Dump file
+*.stackdump
+
+# Folder config file
+[Dd]esktop.ini
+
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+
+# Windows Installer files
+*.cab
+*.msi
+*.msix
+*.msm
+*.msp
+
+# Windows shortcuts
+*.lnk
\ No newline at end of file
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..2708095
--- /dev/null
+++ b/__init__.py
@@ -0,0 +1,4 @@
+from .cartoongan import Cartoongan
+
+def nnoperator_template(*args, **kwargs):
+    return Cartoongan(*args, **kwargs)
\ No newline at end of file
diff --git a/cartoongan.py b/cartoongan.py
new file mode 100644
index 0000000..7534f5d
--- /dev/null
+++ b/cartoongan.py
@@ -0,0 +1,49 @@
+import logging
+import os
+import numpy
+from pathlib import Path
+from PIL import Image as PImage
+from torchvision import transforms
+
+from towhee import register
+from towhee.operator import NNOperator, OperatorFlag
+from towhee.types import arg, to_image_color
+from towhee._types import Image
+import warnings
+warnings.filterwarnings('ignore')
+
+log = logging.getLogger()
+
+
+@register(output_schema=['styled_image'], flag=OperatorFlag.STATELESS | OperatorFlag.REUSEABLE,)
+class Cartoongan(NNOperator):
+    """
+    A one line summary of this class.
+    """
+
+    def __init__(self, model_name: str, framework: str = 'pytorch', device: str = 'cpu') -> None:
+        super().__init__()
+        self._device = device
+        if framework == 'pytorch':
+            import importlib.util
+            path = os.path.join(str(Path(__file__).parent), 'pytorch', 'model.py')
+            opname = os.path.basename(str(Path(__file__))).split('.')[0]
+            spec = importlib.util.spec_from_file_location(opname, path)
+            module = importlib.util.module_from_spec(spec)
+            spec.loader.exec_module(module)
+        self.model = module.Model(model_name, self._device)
+        self.tfms = transforms.Compose([
+            transforms.ToTensor()
+        ])
+
+    @arg(1, to_image_color('RGB'))
+    def __call__(self, image):
+        img = self.tfms(image).unsqueeze(0)
+        styled_image = self.model(img)
+
+        styled_image = numpy.transpose(styled_image, (1, 2, 0))
+        styled_image = PImage.fromarray((styled_image * 255).astype(numpy.uint8))
+        styled_image = numpy.array(styled_image)
+        styled_image = styled_image[:, :, ::-1].copy()
+
+        return Image(styled_image, 'BGR')
\ No newline at end of file
diff --git a/pytorch/__init__.py b/pytorch/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/pytorch/model.py b/pytorch/model.py
new file mode 100644
index 0000000..20e274b
--- /dev/null
+++ b/pytorch/model.py
@@ -0,0 +1,200 @@
+import os
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from pathlib import Path
+
+class Transformer(nn.Module):
+    def __init__(self):
+        super(Transformer, self).__init__()
+        #
+        self.refpad01_1 = nn.ReflectionPad2d(3)
+        self.conv01_1 = nn.Conv2d(3, 64, 7)
+        self.in01_1 = InstanceNormalization(64)
+        # relu
+        self.conv02_1 = nn.Conv2d(64, 128, 3, 2, 1)
+        self.conv02_2 = nn.Conv2d(128, 128, 3, 1, 1)
+        self.in02_1 = InstanceNormalization(128)
+        # relu
+        self.conv03_1 = nn.Conv2d(128, 256, 3, 2, 1)
+        self.conv03_2 = nn.Conv2d(256, 256, 3, 1, 1)   
+        self.in03_1 = InstanceNormalization(256)    
+        # relu
+
+        ## res block 1
+        self.refpad04_1 = nn.ReflectionPad2d(1)
+        self.conv04_1 = nn.Conv2d(256, 256, 3)
+        self.in04_1 = InstanceNormalization(256)
+        # relu
+        self.refpad04_2 = nn.ReflectionPad2d(1)
+        self.conv04_2 = nn.Conv2d(256, 256, 3)
+        self.in04_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 2
+        self.refpad05_1 = nn.ReflectionPad2d(1)
+        self.conv05_1 = nn.Conv2d(256, 256, 3)
+        self.in05_1 = InstanceNormalization(256)
+        # relu
+        self.refpad05_2 = nn.ReflectionPad2d(1)
+        self.conv05_2 = nn.Conv2d(256, 256, 3)
+        self.in05_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 3
+        self.refpad06_1 = nn.ReflectionPad2d(1)
+        self.conv06_1 = nn.Conv2d(256, 256, 3)
+        self.in06_1 = InstanceNormalization(256)
+        # relu
+        self.refpad06_2 = nn.ReflectionPad2d(1)
+        self.conv06_2 = nn.Conv2d(256, 256, 3)
+        self.in06_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 4
+        self.refpad07_1 = nn.ReflectionPad2d(1)
+        self.conv07_1 = nn.Conv2d(256, 256, 3)
+        self.in07_1 = InstanceNormalization(256)
+        # relu
+        self.refpad07_2 = nn.ReflectionPad2d(1)
+        self.conv07_2 = nn.Conv2d(256, 256, 3)
+        self.in07_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 5
+        self.refpad08_1 = nn.ReflectionPad2d(1)
+        self.conv08_1 = nn.Conv2d(256, 256, 3)
+        self.in08_1 = InstanceNormalization(256)
+        # relu
+        self.refpad08_2 = nn.ReflectionPad2d(1)
+        self.conv08_2 = nn.Conv2d(256, 256, 3)
+        self.in08_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 6
+        self.refpad09_1 = nn.ReflectionPad2d(1)
+        self.conv09_1 = nn.Conv2d(256, 256, 3)
+        self.in09_1 = InstanceNormalization(256)
+        # relu
+        self.refpad09_2 = nn.ReflectionPad2d(1)
+        self.conv09_2 = nn.Conv2d(256, 256, 3)
+        self.in09_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 7
+        self.refpad10_1 = nn.ReflectionPad2d(1)
+        self.conv10_1 = nn.Conv2d(256, 256, 3)
+        self.in10_1 = InstanceNormalization(256)
+        # relu
+        self.refpad10_2 = nn.ReflectionPad2d(1)
+        self.conv10_2 = nn.Conv2d(256, 256, 3)
+        self.in10_2 = InstanceNormalization(256)
+        # + input
+
+        ## res block 8
+        self.refpad11_1 = nn.ReflectionPad2d(1)
+        self.conv11_1 = nn.Conv2d(256, 256, 3)
+        self.in11_1 = InstanceNormalization(256)
+        # relu
+        self.refpad11_2 = nn.ReflectionPad2d(1)
+        self.conv11_2 = nn.Conv2d(256, 256, 3)
+        self.in11_2 = InstanceNormalization(256)
+        # + input
+
+        ##------------------------------------##
+        self.deconv01_1 = nn.ConvTranspose2d(256, 128, 3, 2, 1, 1)
+        self.deconv01_2 = nn.Conv2d(128, 128, 3, 1, 1)
+        self.in12_1 = InstanceNormalization(128)
+        # relu
+        self.deconv02_1 = nn.ConvTranspose2d(128, 64, 3, 2, 1, 1)
+        self.deconv02_2 = nn.Conv2d(64, 64, 3, 1, 1)
+        self.in13_1 = InstanceNormalization(64)
+        # relu
+        self.refpad12_1 = nn.ReflectionPad2d(3)
+        self.deconv03_1 = nn.Conv2d(64, 3, 7)
+        # tanh
+
+    def forward(self, x):
+        y = F.relu(self.in01_1(self.conv01_1(self.refpad01_1(x))))
+        y = F.relu(self.in02_1(self.conv02_2(self.conv02_1(y))))
+        t04 = F.relu(self.in03_1(self.conv03_2(self.conv03_1(y))))
+
+        ##
+        y = F.relu(self.in04_1(self.conv04_1(self.refpad04_1(t04))))
+        t05 = self.in04_2(self.conv04_2(self.refpad04_2(y))) + t04
+
+        y = F.relu(self.in05_1(self.conv05_1(self.refpad05_1(t05))))
+        t06 = self.in05_2(self.conv05_2(self.refpad05_2(y))) + t05
+
+        y = F.relu(self.in06_1(self.conv06_1(self.refpad06_1(t06))))
+        t07 = self.in06_2(self.conv06_2(self.refpad06_2(y))) + t06
+
+        y = F.relu(self.in07_1(self.conv07_1(self.refpad07_1(t07))))
+        t08 = self.in07_2(self.conv07_2(self.refpad07_2(y))) + t07
+
+        y = F.relu(self.in08_1(self.conv08_1(self.refpad08_1(t08))))
+        t09 = self.in08_2(self.conv08_2(self.refpad08_2(y))) + t08
+
+        y = F.relu(self.in09_1(self.conv09_1(self.refpad09_1(t09))))
+        t10 = self.in09_2(self.conv09_2(self.refpad09_2(y))) + t09
+
+        y = F.relu(self.in10_1(self.conv10_1(self.refpad10_1(t10))))
+        t11 = self.in10_2(self.conv10_2(self.refpad10_2(y))) + t10
+
+        y = F.relu(self.in11_1(self.conv11_1(self.refpad11_1(t11))))
+        y = self.in11_2(self.conv11_2(self.refpad11_2(y))) + t11
+        ##
+
+        y = F.relu(self.in12_1(self.deconv01_2(self.deconv01_1(y))))
+        y = F.relu(self.in13_1(self.deconv02_2(self.deconv02_1(y))))
+        y = F.tanh(self.deconv03_1(self.refpad12_1(y)))
+
+        return y
+
+
+class InstanceNormalization(nn.Module):
+    def __init__(self, dim, eps=1e-9):
+        super(InstanceNormalization, self).__init__()
+        self.scale = nn.Parameter(torch.FloatTensor(dim))
+        self.shift = nn.Parameter(torch.FloatTensor(dim))
+        self.eps = eps
+        self._reset_parameters()
+
+    def _reset_parameters(self):
+        self.scale.data.uniform_()
+        self.shift.data.zero_()
+
+    def __call__(self, x):
+        n = x.size(2) * x.size(3)
+        t = x.view(x.size(0), x.size(1), n)
+        mean = torch.mean(t, 2).unsqueeze(2).unsqueeze(3).expand_as(x)
+        # Calculate the biased var. torch.var returns unbiased var
+        var = torch.var(t, 2).unsqueeze(2).unsqueeze(3).expand_as(x) * ((n - 1) / float(n))
+        scale_broadcast = self.scale.unsqueeze(1).unsqueeze(1).unsqueeze(0)
+        scale_broadcast = scale_broadcast.expand_as(x)
+        shift_broadcast = self.shift.unsqueeze(1).unsqueeze(1).unsqueeze(0)
+        shift_broadcast = shift_broadcast.expand_as(x)
+        out = (x - mean) / torch.sqrt(var + self.eps)
+        out = out * scale_broadcast + shift_broadcast
+        return out
+
+
+class Model():
+    def __init__(self, model_name, device) -> None:
+        self._device = device
+        self._model = Transformer()
+        path = os.path.join(str(Path(__file__).parent), 'weights', model_name + '_net_G_float.pth')
+        self._model.load_state_dict(torch.load(path))
+        self._model.to(self._device)
+        self._model.eval()
+
+    def __call__(self, img_tensor: Tensor):
+        img_tensor = img_tensor.to(self._device)
+        img_tensor = img_tensor * 2 - 1
+
+        output_image = self._model(img_tensor)
+        output_image = output_image[0]
+        # BGR -> RGB
+        output_image = output_image[[2, 1, 0], :, :]
+        output_image = output_image.data.cpu().float() * 0.5 + 0.5
+        return output_image.numpy()
diff --git a/pytorch/weights/Hayao_net_G_float.pth b/pytorch/weights/Hayao_net_G_float.pth
new file mode 100644
index 0000000..dc4bd11
--- /dev/null
+++ b/pytorch/weights/Hayao_net_G_float.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ab0e492efb3b705487db38679e363dc8b1f016692913bbe100587d695a9e2b5
+size 44529096
diff --git a/pytorch/weights/Hosoda_net_G_float.pth b/pytorch/weights/Hosoda_net_G_float.pth
new file mode 100644
index 0000000..7dd5313
--- /dev/null
+++ b/pytorch/weights/Hosoda_net_G_float.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c666eea7700864d5972765cc43e926d900174648297bfef494006dc230fd1bf0
+size 44529096
diff --git a/pytorch/weights/Paprika_net_G_float.pth b/pytorch/weights/Paprika_net_G_float.pth
new file mode 100644
index 0000000..c8f87bd
--- /dev/null
+++ b/pytorch/weights/Paprika_net_G_float.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0629352a54838e56a2ad7fca3e6e51e6889d4338c37469f9ddb43e5929ef9475
+size 44529096
diff --git a/pytorch/weights/Shinkai_net_G_float.pth b/pytorch/weights/Shinkai_net_G_float.pth
new file mode 100644
index 0000000..8de7435
--- /dev/null
+++ b/pytorch/weights/Shinkai_net_G_float.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 44529096