Add publisher id and tweak description

CHANGELOG.md

@@ -1,7 +1,3 @@
-0.3
-
-* Added img2img node 
-
 0.2 
 
 * Added textbox to change model (must match downloaded model) and dropdown list to choose sampler

README.md

@@ -4,7 +4,7 @@ These nodes provide a wrapper for calling [Draw Things](https://drawthings.ai/)
 
 **Wait, why?** The Draw Things app has been optimized for Apple hardware and runs roughly x3 faster than ComfyUI generations. But ComfyUI is a flexible and powerful tools, and has some features - like queuing and face swapping - that haven't been implemented in Draw Things.
 
-These simple nodes for txt2img and img2img call a local instance of Draw Things through its API and return the resulting image to ComfyUI.
+This simple node calls a local instance of Draw Things through its API and returns the resulting image to ComfyUI.
 
 ![](basic_example.png)
 

__init__.py

@@ -1,3 +1,3 @@
 from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
 
-__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
+__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

nodes.py

@@ -8,7 +8,6 @@ import numpy as np
 import requests
 from PIL import Image
 import io
-from io import BytesIO
 import torch
 
 
@@ -28,28 +27,7 @@ class DrawThingsTxt2Img:
                 "width": ("INT", {"default": 512}),
                 "height": ("INT", {"default": 512}),
                 "guidance_scale": ("FLOAT", {"default": 3.5}),
-                "sampler": (
-                    [
-                        "UniPC",
-                        "DPM++ 2M Karras",
-                        "Euler Ancestral",
-                        "DPM++ SDE Karras",
-                        "PLMS",
-                        "DDIM",
-                        "LCM",
-                        "Euler A Substep",
-                        "DPM++ SDE Substep",
-                        "TCD",
-                        "DPM++ 2M Trailing",
-                        "Euler A Trailing",
-                        "DPM++ SDE Trailing",
-                        "DDIM Trailing",
-                        "DPM++ 2M AYS",
-                        "Euler A AYS",
-                        "DPM++ SDE AYS",
-                    ],
-                    {"default": "Euler A Trailing"},
-                ),
+                "sampler": (["UniPC","DPM++ 2M Karras","Euler Ancestral", "DPM++ SDE Karras", "PLMS", "DDIM", "LCM", "Euler A Substep", "DPM++ SDE Substep", "TCD", "DPM++ 2M Trailing", "Euler A Trailing", "DPM++ SDE Trailing", "DDIM Trailing", "DPM++ 2M AYS", "Euler A AYS", "DPM++ SDE AYS"], {"default": "Euler A Trailing"}),
                 "steps": ("INT", {"default": 20}),
             }
         }
@@ -58,9 +36,7 @@ class DrawThingsTxt2Img:
     RETURN_NAMES = ("generated_image",)
     FUNCTION = "generate_image"
 
-    def generate_image(
-        self, model, prompt, seed, width, height, guidance_scale, sampler, steps
-    ):
+    def generate_image(self, model, prompt, seed, width, height, guidance_scale, sampler, steps):
         # Call the Draw Things API
         api_url = "http://127.0.0.1:7860/sdapi/v1/txt2img"
 
@@ -96,156 +72,6 @@ class DrawThingsTxt2Img:
         return (torch.stack(images),)
 
 
-def image_to_base64(image_tensor):
-    # Convert the image tensor to a NumPy array and scale it to the range 0-255
-    i = 255.0 * image_tensor.cpu().numpy()
-    img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+NODE_CLASS_MAPPINGS = {"DrawThingsTxt2Img": DrawThingsTxt2Img}
 
-    # Save the image to a BytesIO object (in memory) rather than to a file
-    buffered = BytesIO()
-    img.save(buffered, format="PNG")
-
-    # Encode the image as base64
-    encoded_string = base64.b64encode(buffered.getvalue()).decode("utf-8")
-    return encoded_string
-
-
-def resize_for_inpainting(pixels, mask=None):
-    x = (pixels.shape[1] // 64) * 64
-    y = (pixels.shape[2] // 64) * 64
-    # mask = torch.nn.functional.interpolate(mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])), size=(pixels.shape[1], pixels.shape[2]), mode="bilinear")
-
-    orig_pixels = pixels
-    pixels = orig_pixels.clone()
-    if pixels.shape[1] != x or pixels.shape[2] != y:
-        x_offset = (pixels.shape[1] % 64) // 2
-        y_offset = (pixels.shape[2] % 64) // 2
-        pixels = pixels[:, x_offset : x + x_offset, y_offset : y + y_offset, :]
-        # pixels = pixels[:,x_offset:x + x_offset, y_offset:y + y_offset]
-        # mask = mask[:,:,x_offset:x + x_offset, y_offset:y + y_offset]
-
-    # m = (1.0 - mask.round()).squeeze(1)
-    # for i in range(3):
-    #    pixels[:,:,:,i] -= 0.5
-    #    pixels[:,:,:,i] *= m
-    #    pixels[:,:,:,i] += 0.5
-    return pixels
-
-
-def get_image_size(pixels):
-    """
-    Get image size from a size image, i.e. assumed input size is [H, W, C]
-    """
-    x = (pixels.shape[0] // 64) * 64
-    y = (pixels.shape[1] // 64) * 64
-    return x, y
-
-
-class DrawThingsImg2Img:
-    def __init__(self):
-        pass
-
-    CATEGORY = "DrawThingsWrapper"
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "images": ("IMAGE", {"tooltip": "input image"}),
-                "model": ("STRING", {"default": "flux_1_dev_q8p.ckpt"}),
-                "prompt": ("STRING", {"default": ""}),
-                "seed": ("INT", {"default": 42}),
-                "guidance_scale": (
-                    "FLOAT",
-                    {"default": 3.5, "min": 0, "max": 25, "step": 0.1},
-                ),
-                "sampler": (
-                    [
-                        "UniPC",
-                        "DPM++ 2M Karras",
-                        "Euler Ancestral",
-                        "DPM++ SDE Karras",
-                        "PLMS",
-                        "DDIM",
-                        "LCM",
-                        "Euler A Substep",
-                        "DPM++ SDE Substep",
-                        "TCD",
-                        "DPM++ 2M Trailing",
-                        "Euler A Trailing",
-                        "DPM++ SDE Trailing",
-                        "DDIM Trailing",
-                        "DPM++ 2M AYS",
-                        "Euler A AYS",
-                        "DPM++ SDE AYS",
-                    ],
-                    {"default": "Euler A Trailing"},
-                ),
-                "steps": ("INT", {"default": 20, "min": 1, "max": 150, "step": 1}),
-                "denoise": (
-                    "FLOAT",
-                    {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01},
-                ),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("generated_image",)
-    FUNCTION = "generate_image"
-
-    def generate_image(
-        self, images, model, prompt, seed, guidance_scale, sampler, steps, denoise
-    ):
-        # Call the Draw Things API
-        api_url = "http://127.0.0.1:7860/sdapi/v1/img2img"
-
-        encoded_images = []
-        images_resized = resize_for_inpainting(images)
-        for image_tensor in images_resized:
-            encoded_images.append(image_to_base64(image_tensor))
-
-        height, width = get_image_size(images_resized[0])
-
-        payload = {
-            "model": model,
-            "prompt": prompt,
-            "seed": seed,
-            "width": width,
-            "height": height,
-            "guidance_scale": guidance_scale,
-            "sampler": sampler,
-            "steps": steps,
-            "init_images": encoded_images,
-            "strength": denoise,
-        }
-
-        response = requests.post(api_url, json=payload)
-
-        # Raise an error if the request failed
-        response.raise_for_status()
-
-        # Parse the JSON response
-        data = response.json()
-
-        # Process the images (assuming they are base64 encoded or raw binary data)
-        images = []
-        for img_data in data["images"]:
-            image_bytes = base64.b64decode(img_data)
-            # Convert the image data to a Pillow Image object
-            image = Image.open(io.BytesIO(image_bytes))
-            image_np = np.array(image)
-            # Convert to float32 tensor and normalize
-            tensor_image = torch.from_numpy(image_np.astype(np.float32) / 255.0)
-            images.append(tensor_image)
-        return (torch.stack(images),)
-
-
-NODE_CLASS_MAPPINGS = {
-    "DrawThingsTxt2Img": DrawThingsTxt2Img,
-    "DrawThingsImg2Img": DrawThingsImg2Img,
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "DrawThingsTxt2Img": "Draw Things Txt2Img",
-    "DrawThingsImg2Img": "Draw Things Img2Img",
-}
+NODE_DISPLAY_NAME_MAPPINGS = {"DrawThingsTxt2Img": "Draw Things Txt2Img"}

pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "comfyui-drawthingswrapper"
+description = "These nodes provide a wrapper for calling Draw Things image generations from ComfyUI. The Draw Things app has been optimized for Apple hardware and runs roughly x3 faster than ComfyUI generations. But ComfyUI is a flexible and powerful tool, and has some features - like queuing and face swapping - that haven't been implemented in Draw Things."
+version = "1.0.0"
+license = {file = "LICENSE"}
+dependencies = ["numpy", "PIL", "requests", "torch"]
+
+[project.urls]
+Repository = "https://github.com/JosephThomasParker/ComfyUI-DrawThingsWrapper"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "seosamh"
+DisplayName = "ComfyUI-DrawThingsWrapper"
+Icon = ""