fork: custom nodes for doodle project

.gitignore

@@ -5,7 +5,7 @@ __pycache__/
 !/input/example.png
 /models/
 /temp/
-/custom_nodes/
+#/custom_nodes/
 !custom_nodes/example_node.py.example
 extra_model_paths.yaml
 /.vs
@@ -15,4 +15,5 @@ venv/
 !/web/extensions/logging.js.example
 !/web/extensions/core/
 /tests-ui/data/object_info.json
-/user/
+/user/
+*.log

.vscode/settings.json

@@ -0,0 +1,2 @@
+{
+}

custom_nodes/doodle-tiles-node/__init__.py

@@ -0,0 +1,125 @@
+from PIL import Image, ImageOps, ImageFilter
+import numpy as np
+import random
+from skimage.restoration import denoise_nl_means, estimate_sigma
+from skimage import img_as_float, img_as_ubyte
+import torch
+
+# Tensor to PIL
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# PIL to Tensor
+def pil2tensor(image):
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+
+class DoodleTilesGenerator:
+    """
+    A node for creating a mosaic image with solid color background and black & white tiles merged such that
+    white areas become transparent and black areas retain color.
+
+    This node applies a denoising filter to enhance tile quality and resizes tiles for a unique artistic effect.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """
+        Define input types for ComfyUI node.
+        """
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "tile_width": ("INT", {
+                    "default": 128,
+                    "min": 1,
+                    "max": 1024,
+                    "step": 1,
+                }),
+                "tile_height": ("INT", {
+                    "default": 128,
+                    "min": 1,
+                    "max": 1024,
+                    "step": 1,
+                }),
+                "bg_width": ("INT", {
+                    "default": 1024,
+                    "min": 100,
+                    "max": 5000,
+                    "step": 1,
+                }),
+                "bg_height": ("INT", {
+                    "default": 1024,
+                    "min": 100,
+                    "max": 5000,
+                    "step": 1,
+                }),
+                "bg_color": ("STRING", {
+                    "default": "(254, 80, 0)",
+                    "multiline": False,
+                }),
+                "stroke_color": ("STRING", {
+                    "default": "(171, 54, 0)",
+                    "multiline": False,
+                })
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("images",)
+    FUNCTION = "create_mosaic"
+    CATEGORY = "image"
+
+    def create_mosaic(self, images, tile_width, tile_height, bg_width, bg_height, bg_color, stroke_color):        
+        # Process the background color string input
+        bg_color = eval(bg_color)
+
+        # Process the stroke color string input
+        stroke_color = eval(stroke_color)
+
+        # Create a solid color background image
+        background = Image.new('RGBA', (bg_width, bg_height), color=bg_color)
+
+        # Load tiles and prepare masks
+        tiles = []
+        for image in images:
+            original_tile = tensor2pil(image).convert('L')
+            resized_tile = original_tile.resize((int(tile_width * 0.8), int(tile_height * 0.8)), Image.LANCZOS)
+            mask = resized_tile.point(lambda p: p <= 128 and 255)
+            tile_image = ImageOps.colorize(resized_tile, stroke_color, stroke_color)
+
+            np_image = np.array(tile_image)
+            float_image = img_as_float(np_image)
+            sigma_est = np.mean(estimate_sigma(float_image, channel_axis=-1))
+            denoised_image = denoise_nl_means(float_image, h=2.0 * sigma_est, fast_mode=True,
+                                                patch_size=7, patch_distance=11, channel_axis=-1)
+            denoised_tile = Image.fromarray(img_as_ubyte(denoised_image))
+            denoised_tile = denoised_tile.filter(ImageFilter.EDGE_ENHANCE_MORE)
+
+            centered_tile = Image.new('RGBA', (tile_width, tile_height), bg_color+(0,))
+            centered_mask = Image.new('L', (tile_width, tile_height), 0)
+            top_left_corner = ((tile_width - denoised_tile.width) // 2, (tile_height - denoised_tile.height) // 2)
+            centered_tile.paste(denoised_tile, top_left_corner)
+            centered_mask.paste(mask, top_left_corner)
+
+            tiles.append((centered_tile, centered_mask))
+
+        random.shuffle(tiles)
+
+        # Place tiles on the background using masks
+        num_tiles_x = int(np.ceil(bg_width / tile_width))
+        num_tiles_y = int(np.ceil(bg_height / tile_height))
+
+        for y in range(num_tiles_y):
+            for x in range(num_tiles_x):
+                tile, mask = tiles[(x + y * num_tiles_x) % len(tiles)]
+                background.paste(tile, (x * tile_width, y * tile_height), mask)
+
+        # Convert the final PIL image to a format that ComfyUI can handle as an output
+        output_image = pil2tensor(background)
+        return (output_image,)
+
+# A dictionary that contains all nodes you want to export with their names
+# NOTE: names should be globally unique
+NODE_CLASS_MAPPINGS = {
+    "Doodle Tiles Generator": DoodleTilesGenerator
+}

custom_nodes/doodle-tiles-node/requirements.txt

@@ -0,0 +1,3 @@
+numpy==1.26.4
+Pillow==10.3.0
+scikit-image==0.22.0

execution.py

@@ -430,6 +430,7 @@ def validate_inputs(prompt, item, validated):
                     "input_name": x
                 }
             }
+
             errors.append(error)
             continue
 

requirements.conda.txt

@@ -0,0 +1,216 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+_libgcc_mutex=0.1=main
+_openmp_mutex=5.1=1_gnu
+absl-py=2.1.0=pypi_0
+accelerate=0.29.3=pypi_0
+addict=2.4.0=pypi_0
+aiohttp=3.9.4=pypi_0
+aiosignal=1.3.1=pypi_0
+annotated-types=0.6.0=pypi_0
+antlr4-python3-runtime=4.9.3=pypi_0
+anyio=4.3.0=pypi_0
+asttokens=2.4.1=pypi_0
+async-timeout=4.0.3=pypi_0
+attrs=23.2.0=pypi_0
+ca-certificates=2024.3.11=h06a4308_0
+cachetools=5.3.3=pypi_0
+certifi=2024.2.2=pypi_0
+cffi=1.16.0=pypi_0
+charset-normalizer=3.3.2=pypi_0
+click=8.1.7=pypi_0
+cmake=3.29.2=pypi_0
+coloredlogs=15.0.1=pypi_0
+colour-science=0.4.4=pypi_0
+comfy-script=0.4.6=pypi_0
+comfyui-ib-customnodes=0.2.2=pypi_0
+comfyui-tooling-nodes=0.1.0=pypi_0
+comm=0.2.2=pypi_0
+contourpy=1.2.1=pypi_0
+cstr=0.1.0=pypi_0
+cycler=0.12.1=pypi_0
+datasets=2.19.0=pypi_0
+decorator=5.1.1=pypi_0
+diffusers=0.27.2=pypi_0
+dill=0.3.8=pypi_0
+einops=0.7.0=pypi_0
+exceptiongroup=1.2.1=pypi_0
+executing=2.0.1=pypi_0
+fairscale=0.4.13=pypi_0
+fastapi=0.110.2=pypi_0
+ffmpy=0.3.0=pypi_0
+filelock=3.13.4=pypi_0
+flatbuffers=24.3.25=pypi_0
+fonttools=4.51.0=pypi_0
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+fsspec=2024.3.1=pypi_0
+gitdb=4.0.11=pypi_0
+gitpython=3.1.43=pypi_0
+google-ai-generativelanguage=0.6.2=pypi_0
+google-api-core=2.18.0=pypi_0
+google-api-python-client=2.126.0=pypi_0
+google-auth=2.29.0=pypi_0
+google-auth-httplib2=0.2.0=pypi_0
+google-generativeai=0.5.2=pypi_0
+googleapis-common-protos=1.63.0=pypi_0
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+httplib2=0.22.0=pypi_0
+httpx=0.27.0=pypi_0
+huggingface-hub=0.22.2=pypi_0
+humanfriendly=10.0=pypi_0
+idna=3.7=pypi_0
+image-reward=1.5=pypi_0
+imageio=2.34.0=pypi_0
+imageio-ffmpeg=0.4.9=pypi_0
+img2texture=1.0.6=pypi_0
+importlib-metadata=7.1.0=pypi_0
+importlib-resources=6.4.0=pypi_0
+ipython=8.18.1=pypi_0
+ipywidgets=8.1.2=pypi_0
+jax=0.4.26=pypi_0
+jaxlib=0.4.26=pypi_0
+jedi=0.19.1=pypi_0
+jinja2=3.1.3=pypi_0
+joblib=1.4.0=pypi_0
+jsonschema=4.21.1=pypi_0
+jsonschema-specifications=2023.12.1=pypi_0
+jupyterlab-widgets=3.0.10=pypi_0
+kiwisolver=1.4.5=pypi_0
+kornia=0.7.2=pypi_0
+kornia-rs=0.1.3=pypi_0
+lazy-loader=0.4=pypi_0
+ld_impl_linux-64=2.38=h1181459_1
+libffi=3.4.4=h6a678d5_0
+libgcc-ng=11.2.0=h1234567_1
+libgomp=11.2.0=h1234567_1
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+multidict=6.0.5=pypi_0
+multiprocess=0.70.16=pypi_0
+ncurses=6.4=h6a678d5_0
+nest-asyncio=1.6.0=pypi_0
+networkx=3.2.1=pypi_0
+numba=0.59.1=pypi_0
+numpy=1.26.4=pypi_0
+nvidia-cublas-cu12=12.1.3.1=pypi_0
+nvidia-cuda-cupti-cu12=12.1.105=pypi_0
+nvidia-cuda-nvrtc-cu12=12.1.105=pypi_0
+nvidia-cuda-runtime-cu12=12.1.105=pypi_0
+nvidia-cudnn-cu12=8.9.2.26=pypi_0
+nvidia-cufft-cu12=11.0.2.54=pypi_0
+nvidia-curand-cu12=10.3.2.106=pypi_0
+nvidia-cusolver-cu12=11.4.5.107=pypi_0
+nvidia-cusparse-cu12=12.1.0.106=pypi_0
+nvidia-nccl-cu12=2.19.3=pypi_0
+nvidia-nvjitlink-cu12=12.4.127=pypi_0
+nvidia-nvtx-cu12=12.1.105=pypi_0
+ollama=0.1.9=pypi_0
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