Initial Commit

2023-08-18 18:45:47 -04:00
parent ce4a39b532
commit ff352f4843
5 changed files with 437 additions and 1 deletions
@@ -0,0 +1,177 @@
+isnet/
+
+# Other GitIgnore Templates:
+
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
+# 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/
@@ -1,2 +1,11 @@
 # ComfyUI-TeaNodes
- 
+
+Adds a few new nodes:
+
+Image Equalization CLAHE style.
+
+Image Size Approximation based on pixel count that retains Image ratio.
+
+Image Resize Node that takes size tuple from Size Approximation Node.
+
+Image Scale Node that simply multiplies image size by a factor.
@@ -0,0 +1,13 @@
+from .nodes import NODE_CLASS_MAPPINGS as NCM
+
+
+NODE_CLASS_MAPPINGS = {
+    **NCM,
+}
+
+def remove_cm_prefix(node_mapping: str) -> str:
+    if node_mapping.startswith("TC_"):
+        return node_mapping[3:]
+    return node_mapping
+
+NODE_DISPLAY_NAME_MAPPINGS = {key: remove_cm_prefix(key) for key in NODE_CLASS_MAPPINGS}
@@ -0,0 +1,43 @@
+
+from math import ceil, floor, log
+
+debouncer = set()
+
+def po2(value, fill=False):
+    func = ceil if fill else floor
+    return pow(2, func(log(value)/log(2)))
+
+def pixel_approx(primary, secondary, total=1024, ratio=1.0,
+                 threshold=0.125, _inc=1024, calculate_inc=True) -> tuple:
+    global debouncer
+    if calculate_inc:
+        debouncer.clear()
+        total *= total
+        ratio = secondary / primary
+        primary = po2(primary)
+        secondary = primary * ratio
+        _inc = primary / 4
+    elif total * 3 > int(primary * secondary) > total * 0.333:
+        if abs(_inc) >= 64: _inc /= 2
+
+    # print(f"Action: {_inc}")
+
+    count = round(primary) * round(secondary)
+    # print(round(primary), round(secondary), count)
+
+    _recurse = False
+    if count > total:
+        _inc = abs(_inc) * -1
+    elif count < total:
+        _inc = abs(_inc)
+
+    if not (total * (1+threshold) > count > total * (1-threshold)) and total not in debouncer:
+        debouncer.add(count)
+        _recurse = True
+
+    if _recurse:
+        primary += _inc
+        secondary = primary * ratio
+        primary, secondary = pixel_approx(primary, secondary, total, ratio, threshold, _inc, False)
+
+    return (int(primary), int(secondary))
@@ -0,0 +1,194 @@
+import os, torch
+import numpy as np
+import comfy.utils
+
+from kornia.enhance import equalize_clahe
+from ._func import pixel_approx, po2
+# from .isnet import dis_process
+from PIL import Image
+
+class EqualizeCLAHE:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE", ),
+                "clip_limit": ("FLOAT", {"default": 64, "min": 0.0, "max": 255, "step": 0.1}),
+                "grid_size": ("INT", {"default": 8, "min": 1, "max": 64, "step": 1}),
+            },
+            "optional": {
+                "size": ("TUPLE", {"default": (1024, 1024)}),
+            }
+        }
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "equalize"
+    CATEGORY = "TeaNodes/Image"
+
+    def equalize(self, image, size, clip_limit, grid_size):
+        _image = image.movedim(-1, 1)
+        if size != (1024, 1024):
+            grid_ratio = grid_size / clip_limit
+            size_ratio = min(size) / max(size)
+            clip_limit = po2(max(size), True)
+            grid_x = clip_limit * grid_ratio
+            grid_y = max(2, grid_x * size_ratio // 2 * 2)
+            if size[0] < size[1]: grid_x, grid_y = grid_y, grid_x
+        _image = equalize_clahe(_image, clip_limit, (grid_x, grid_y))
+        result = _image.movedim(1, -1)
+
+        return (result,)
+
+class SizeApproximation:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "square": ("INT", {"default": 1024, "min": 512, "max": 4096, "step": 32}),
+        }
+    }
+
+    RETURN_TYPES = ("TUPLE", "INT", "INT")
+    FUNCTION = "calculate"
+    CATEGORY = "TeaNodes/Image"
+
+    def calculate(self, image, square):
+        _image = image.movedim(-1, 1)
+
+        height, width = image.shape[1:3]
+
+        # print(width, height)
+
+        if width >= height:
+            width, height = pixel_approx(width, height, square)
+        else:
+            height, width = pixel_approx(height, width, square)
+
+        return ((width, height), width, height)
+
+
+class ImageResize:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "width": ("INT", {"default": 1024, "min": 512, "max": 4096, "step": 32}),
+                "height": ("INT", {"default": 1024, "min": 512, "max": 4096, "step": 32}),
+            },
+            "optional": {
+                "size": ("TUPLE", {"default": (1024, 1024)}),
+            }
+    }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "resize"
+    CATEGORY = "TeaNodes/Image"
+
+    def resize(self, image, size, width, height):
+        _image = image.movedim(-1, 1)
+
+        if size != (1024, 1024): width, height = size
+
+        result = comfy.utils.common_upscale(_image, int( width ), int( height ), "area", 'center')
+        result = result.movedim(1, -1)
+        return (result,)
+
+class ImageScale:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "factor": ("FLOAT", {"default": 1.0, "min": 0.2, "max": 5.0, "step": 0.01}),
+        }
+    }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "resize"
+    CATEGORY = "TeaNodes/Image"
+
+    def resize(self, image, factor):
+        _image = image.movedim(-1, 1)
+
+        height, width = image.shape[1:3]
+
+        result = comfy.utils.common_upscale(_image, int( width * factor ), int( height * factor ), "area", 'center')
+        result = result.movedim(1, -1)
+
+        return (result,)
+
+class ColorFill():
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "color": ("STRING", {"default": '#7f7f7fff'}),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "fill"
+    CATEGORY = "TeaNodes/Input"
+
+    def fill(self, image, color):
+        if color.startswith('#'):
+            _color = color.lstrip('#')
+            try: color_rgba = tuple(int(_color[i:i+2], 16) for i in (0, 2, 4, 6))
+            except: color_rgba = tuple(int(_color[i:i+2], 16) for i in (0, 2, 4))
+            else: print(f"Something went wrong here: {color}")
+        else:
+            _color = color.split(',')
+            try: _color = tuple(int(e) for e in _color if 255>int(e)>0)
+            except: print(f"Something went wrong here: {color}")
+            color_rgba = _color
+        color_mode = 'RGBA' if len(color_rgba) > 3 else 'RGB'
+
+        height, width = image.shape[1:3]
+
+        _image = Image.new('RGBA', (width, height), color_rgba)
+        _image = np.array(_image.convert(color_mode)).astype(np.float32) / 255.0
+        result = torch.from_numpy(_image).unsqueeze(0)
+
+        return (result,)
+
+# class MaskBG_DIS:
+#     @classmethod
+#     def INPUT_TYPES(s):
+#         return {
+#             "required": {
+#                 "image": ("IMAGE", ),
+#             }
+#         }
+
+#     RETURN_TYPES = ("IMAGE",)
+#     FUNCTION = "process"
+#     CATEGORY = "TeaNodes/Image"
+
+#     def process(self, image):
+#         i = 255. * image[-1].numpy()
+#         img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+
+#         img.save("..\__temp__.png", format='png', pnginfo=None, compress_level=4)
+
+#         images_transformed = dis_process("..\__temp__.png")
+
+#         os.remove("..\__temp__.png")
+
+#         _image = Image.fromarray(images_transformed)
+
+#         _image = _image.image_to_tensor()
+#         _image.unsqueeze_(0)
+#         result = _image.repeat(1,1,1,3)
+
+#         return (result,)
+
+NODE_CLASS_MAPPINGS = {
+    "TC_EqualizeCLAHE": EqualizeCLAHE,
+    "TC_SizeApproximation": SizeApproximation,
+    "TC_ImageResize": ImageResize,
+    "TC_ImageScale": ImageScale,
+    "TC_ColorFill": ColorFill,
+    # "TC_MaskBG_DIS": MaskBG_DIS,
+}