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6 changed files with 184 additions and 21 deletions
+4
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@@ -1,3 +1,7 @@
0.3
* Added img2img node
0.2 0.2
* Added textbox to change model (must match downloaded model) and dropdown list to choose sampler * Added textbox to change model (must match downloaded model) and dropdown list to choose sampler
+1 -1
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@@ -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. **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.
This simple node calls a local instance of Draw Things through its API and returns the resulting image to ComfyUI. These simple nodes for txt2img and img2img call a local instance of Draw Things through its API and return the resulting image to ComfyUI.
![](basic_example.png) ![](basic_example.png)
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+178 -4
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@@ -8,6 +8,7 @@ import numpy as np
import requests import requests
from PIL import Image from PIL import Image
import io import io
from io import BytesIO
import torch import torch
@@ -27,7 +28,28 @@ class DrawThingsTxt2Img:
"width": ("INT", {"default": 512}), "width": ("INT", {"default": 512}),
"height": ("INT", {"default": 512}), "height": ("INT", {"default": 512}),
"guidance_scale": ("FLOAT", {"default": 3.5}), "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}), "steps": ("INT", {"default": 20}),
} }
} }
@@ -36,7 +58,9 @@ class DrawThingsTxt2Img:
RETURN_NAMES = ("generated_image",) RETURN_NAMES = ("generated_image",)
FUNCTION = "generate_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 # Call the Draw Things API
api_url = "http://127.0.0.1:7860/sdapi/v1/txt2img" api_url = "http://127.0.0.1:7860/sdapi/v1/txt2img"
@@ -72,6 +96,156 @@ class DrawThingsTxt2Img:
return (torch.stack(images),) return (torch.stack(images),)
NODE_CLASS_MAPPINGS = {"DrawThingsTxt2Img": DrawThingsTxt2Img} 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_DISPLAY_NAME_MAPPINGS = {"DrawThingsTxt2Img": "Draw Things Txt2Img"} # 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",
}
-15
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@@ -1,15 +0,0 @@
[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 = ""