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Author SHA1 Message Date
nick f5940ac899 better 2024-08-20 19:43:04 -07:00
nick 67703abb8a syntax 2024-08-20 19:41:23 -07:00
nick dfee31f0ed fix: noise seed 2024-08-20 19:36:29 -07:00
30 changed files with 601 additions and 3356 deletions
+1 -2
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@@ -1,3 +1,2 @@
__pycache__
.DS_Store
file-hash-cache.json
.DS_Store
-3
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@@ -2,9 +2,6 @@
Open source comfyui deployment platform, a `vercel` for generative workflow infra. (serverless hosted gpu with vertical intergation with comfyui)
> [!NOTE]
> Im looking for creative hacker to join ComfyDeploy's core team! DM me on [twitter](https://x.com/BennyKokMusic)
Join [Discord](https://discord.gg/EEYcQmdYZw) to chat more or visit [Comfy Deploy](https://comfydeploy.com/) to get started!
Check out our latest [nextjs starter kit](https://github.com/BennyKok/comfyui-deploy-next-example) with Comfy Deploy
-57
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@@ -1,57 +0,0 @@
import os
import io
import torchaudio
from folder_paths import get_annotated_filepath
class ComfyUIDeployExternalAudio:
RETURN_TYPES = ("AUDIO",)
RETURN_NAMES = ("audio",)
FUNCTION = "load_audio"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": "input_audio"},
),
"audio_file": ("STRING", {"default": ""}),
},
"optional": {
"default_value": ("AUDIO",),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": False, "default": ""},
),
}
}
@classmethod
def VALIDATE_INPUTS(s, audio_file, **kwargs):
return True
def load_audio(self, input_id, audio_file, default_value=None, display_name=None, description=None):
if audio_file and audio_file != "":
if audio_file.startswith(('http://', 'https://')):
# Handle URL input
import requests
response = requests.get(audio_file)
audio_data = io.BytesIO(response.content)
waveform, sample_rate = torchaudio.load(audio_data)
else:
# Handle local file
audio_path = get_annotated_filepath(audio_file)
waveform, sample_rate = torchaudio.load(audio_path)
audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
return (audio,)
else:
return (default_value,)
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"}
+2 -2
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@@ -12,11 +12,11 @@ class ComfyUIDeployExternalBoolean:
"optional": {
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
+2 -2
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@@ -25,11 +25,11 @@ class ComfyUIDeployExternalCheckpoint:
"default_value": (folder_paths.get_filename_list("checkpoints"), ),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
-109
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@@ -1,109 +0,0 @@
import os
import io
import cv2 as cv
import numpy as np
import torch
import requests
from folder_paths import get_annotated_filepath
class ComfyUIDeployExternalEXR:
RETURN_TYPES = ("IMAGE", "MASK")
RETURN_NAMES = ("image", "mask")
FUNCTION = "load_exr"
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": "input_exr"},
),
"exr_file": ("STRING", {"default": ""}),
"tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
},
"optional": {
"default_image": ("IMAGE",),
"default_mask": ("MASK",),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": False, "default": ""},
),
}
}
@classmethod
def VALIDATE_INPUTS(s, exr_file, **kwargs):
return True
def sRGBtoLinear(self, npArray):
less = npArray <= 0.0404482362771082
npArray[less] = npArray[less] / 12.92
npArray[~less] = np.power((npArray[~less] + 0.055) / 1.055, 2.4)
def linearToSRGB(self, npArray):
less = npArray <= 0.0031308
npArray[less] = npArray[less] * 12.92
npArray[~less] = np.power(npArray[~less], 1/2.4) * 1.055 - 0.055
def load_exr(self, input_id, exr_file, tonemap="sRGB",
default_image=None, default_mask=None,
display_name=None, description=None):
try:
if exr_file and exr_file != "":
if exr_file.startswith(('http://', 'https://')):
# Handle URL input
response = requests.get(exr_file)
# Write to temp buffer
buffer = io.BytesIO(response.content)
nparr = np.frombuffer(buffer.getvalue(), np.uint8)
image = cv.imdecode(nparr, cv.IMREAD_UNCHANGED).astype(np.float32)
else:
# Handle local file
exr_path = get_annotated_filepath(exr_file)
image = cv.imread(exr_path, cv.IMREAD_UNCHANGED).astype(np.float32)
if len(image.shape) == 2:
image = np.repeat(image[..., np.newaxis], 3, axis=2)
# Extract RGB and flip channels
rgb = np.flip(image[:,:,:3], 2).copy()
# Apply tonemapping
if tonemap == "sRGB":
self.linearToSRGB(rgb)
rgb = np.clip(rgb, 0, 1)
elif tonemap == "Reinhard":
rgb = np.clip(rgb, 0, None)
rgb = rgb / (rgb + 1)
self.linearToSRGB(rgb)
rgb = np.clip(rgb, 0, 1)
rgb = torch.unsqueeze(torch.from_numpy(rgb), 0)
# Handle alpha/mask
mask = torch.zeros((1, image.shape[0], image.shape[1]), dtype=torch.float32)
if image.shape[2] > 3:
mask[0] = torch.from_numpy(np.clip(image[:,:,3], 0, 1))
return (rgb, mask)
else:
# Return defaults if no file provided
return (default_image, default_mask)
except Exception as e:
print(f"Error loading EXR: {str(e)}")
# Return defaults on error
return (default_image, default_mask)
NODE_CLASS_MAPPINGS = {
"ComfyUIDeployExternalEXR": ComfyUIDeployExternalEXR
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyUIDeployExternalEXR": "External EXR (ComfyUI Deploy)"
}
-108
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@@ -1,108 +0,0 @@
from PIL import Image, ImageOps
import numpy as np
import torch
import folder_paths
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
WILDCARD = AnyType("*")
class ComfyUIDeployExternalFaceModel:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": "input_reactor_face_model"},
),
},
"optional": {
"default_face_model_name": (
"STRING",
{"multiline": False, "default": ""},
),
"face_model_save_name": ( # if `default_face_model_name` is a link to download a file, we will attempt to save it with this name
"STRING",
{"multiline": False, "default": ""},
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
"face_model_url": (
"STRING",
{"multiline": False, "default": ""},
),
},
}
RETURN_TYPES = (WILDCARD,)
RETURN_NAMES = ("path",)
FUNCTION = "run"
CATEGORY = "deploy"
def run(
self,
input_id,
default_face_model_name=None,
face_model_save_name=None,
display_name=None,
description=None,
face_model_url=None,
):
import requests
import os
import uuid
if face_model_url and face_model_url.startswith("http"):
if face_model_save_name:
existing_face_models = folder_paths.get_filename_list("reactor/faces")
# Check if face_model_save_name exists in the list
if face_model_save_name in existing_face_models:
print(f"using face model: {face_model_save_name}")
return (face_model_save_name,)
else:
face_model_save_name = str(uuid.uuid4()) + ".safetensors"
print(face_model_save_name)
print(folder_paths.folder_names_and_paths["reactor/faces"][0][0])
destination_path = os.path.join(
folder_paths.folder_names_and_paths["reactor/faces"][0][0],
face_model_save_name,
)
print(destination_path)
print(
"Downloading external face model - "
+ face_model_url
+ " to "
+ destination_path
)
response = requests.get(
face_model_url,
headers={"User-Agent": "Mozilla/5.0"},
allow_redirects=True,
)
with open(destination_path, "wb") as out_file:
out_file.write(response.content)
return (face_model_save_name,)
else:
print(f"using face model: {default_face_model_name}")
return (default_face_model_name,)
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalFaceModel": ComfyUIDeployExternalFaceModel}
NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyUIDeployExternalFaceModel": "External Face Model (ComfyUI Deploy)"
}
+27 -40
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@@ -17,13 +17,12 @@ class ComfyUIDeployExternalImage:
"default_value": ("IMAGE",),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
"default_value_url": ("STRING", {"image_preview": True, "default": ""}),
}
}
@@ -34,44 +33,32 @@ class ComfyUIDeployExternalImage:
CATEGORY = "image"
def run(self, input_id, default_value=None, display_name=None, description=None, default_value_url=None):
def run(self, input_id, default_value=None, display_name=None, description=None):
image = default_value
# Try both input_id and default_value_url
urls_to_try = [url for url in [input_id, default_value_url] if url]
print(default_value_url)
for url in urls_to_try:
try:
if url.startswith('http'):
import requests
from io import BytesIO
print(f"Fetching image from url: {url}")
response = requests.get(url)
image = Image.open(BytesIO(response.content))
break
elif url.startswith(('data:image/png;base64,', 'data:image/jpeg;base64,', 'data:image/jpg;base64,')):
import base64
from io import BytesIO
print("Decoding base64 image")
base64_image = url[url.find(",")+1:]
decoded_image = base64.b64decode(base64_image)
image = Image.open(BytesIO(decoded_image))
break
except:
continue
if image is not None:
try:
image = ImageOps.exif_transpose(image)
image = image.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
except:
pass
return [image]
try:
if input_id.startswith('http'):
import requests
from io import BytesIO
print("Fetching image from url: ", input_id)
response = requests.get(input_id)
image = Image.open(BytesIO(response.content))
elif input_id.startswith('data:image/png;base64,') or input_id.startswith('data:image/jpeg;base64,') or input_id.startswith('data:image/jpg;base64,'):
import base64
from io import BytesIO
print("Decoding base64 image")
base64_image = input_id[input_id.find(",")+1:]
decoded_image = base64.b64decode(base64_image)
image = Image.open(BytesIO(decoded_image))
else:
raise ValueError("Invalid image url provided.")
image = ImageOps.exif_transpose(image)
image = image.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
return [image]
except:
return [image]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImage": ComfyUIDeployExternalImage}
+2 -2
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@@ -17,11 +17,11 @@ class ComfyUIDeployExternalImageAlpha:
"default_value": ("IMAGE",),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
+4 -24
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@@ -23,11 +23,11 @@ class ComfyUIDeployExternalImageBatch:
"default_value": ("IMAGE",),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
@@ -39,34 +39,14 @@ class ComfyUIDeployExternalImageBatch:
CATEGORY = "image"
def process_image(self, image):
image = ImageOps.exif_transpose(image)
image = image.convert("RGB")
image = np.array(image).astype(np.float32) / 255.0
image_tensor = torch.from_numpy(image)[None,]
return image_tensor
def run(self, input_id, images=None, default_value=None, display_name=None, description=None):
import requests
import zipfile
import io
processed_images = []
try:
images_list = json.loads(images) # Assuming images is a JSON array string
print(images_list)
for img_input in images_list:
if img_input.startswith('http') and img_input.endswith('.zip'):
print("Fetching zip file from url: ", img_input)
response = requests.get(img_input)
zip_file = zipfile.ZipFile(io.BytesIO(response.content))
for file_name in zip_file.namelist():
if file_name.lower().endswith(('.png', '.jpg', '.jpeg')):
with zip_file.open(file_name) as file:
image = Image.open(file)
image = self.process_image(image)
processed_images.append(image)
elif img_input.startswith('http'):
if img_input.startswith('http'):
import requests
from io import BytesIO
print("Fetching image from url: ", img_input)
response = requests.get(img_input)
+29 -51
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@@ -25,21 +25,17 @@ class ComfyUIDeployExternalLora:
},
"optional": {
"default_lora_name": (folder_paths.get_filename_list("loras"),),
"lora_save_name": ( # if `default_lora_name` is a link to download a file, we will attempt to save it with this name
"lora_save_name": ( # if `default_lora_name` is a link to download a file, we will attempt to save it with this name
"STRING",
{"multiline": False, "default": ""},
),
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
"lora_url": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
},
}
@@ -51,55 +47,37 @@ class ComfyUIDeployExternalLora:
CATEGORY = "deploy"
def run(
self,
input_id,
default_lora_name=None,
lora_save_name=None,
display_name=None,
description=None,
lora_url=None,
):
def run(self, input_id, default_lora_name=None, lora_save_name=None, display_name=None, description=None):
import requests
import os
import uuid
if lora_url:
if lora_url.startswith("http"):
if lora_save_name:
existing_loras = folder_paths.get_filename_list("loras")
# Check if lora_save_name exists in the list
if lora_save_name in existing_loras:
print(f"using lora: {lora_save_name}")
return (lora_save_name,)
else:
lora_save_name = str(uuid.uuid4()) + ".safetensors"
print(lora_save_name)
print(folder_paths.folder_names_and_paths["loras"][0][0])
destination_path = os.path.join(
folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
)
print(destination_path)
print(
"Downloading external lora - "
+ lora_url
+ " to "
+ destination_path
)
response = requests.get(
lora_url,
headers={"User-Agent": "Mozilla/5.0"},
allow_redirects=True,
)
with open(destination_path, "wb") as out_file:
out_file.write(response.content)
print(f"Ext Lora loading: {lora_url} to {lora_save_name}")
return (lora_save_name,)
if default_lora_name.startswith("http"):
if lora_save_name:
existing_loras = folder_paths.get_filename_list("loras")
# Check if lora_save_name exists in the list
if lora_save_name in existing_loras:
print(f"using lora: {lora_save_name}")
return (lora_save_name,)
else:
print(f"Ext Lora loading: {lora_url}")
return (lora_url,)
lora_save_name = str(uuid.uuid4()) + ".safetensors"
print(lora_save_name)
print(folder_paths.folder_names_and_paths["loras"][0][0])
destination_path = os.path.join(
folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
)
print(destination_path)
print("Downloading external lora - " + input_id + " to " + destination_path)
response = requests.get(
input_id,
headers={"User-Agent": "Mozilla/5.0"},
allow_redirects=True,
)
with open(destination_path, "wb") as out_file:
out_file.write(response.content)
return (lora_save_name,)
else:
print(f"Ext Lora loading: {default_lora_name}")
print(f"using lora: {default_lora_name}")
return (default_lora_name,)
+2 -2
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@@ -20,11 +20,11 @@ class ComfyUIDeployExternalNumber:
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
+2 -2
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@@ -20,11 +20,11 @@ class ComfyUIDeployExternalNumberInt:
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
+2 -2
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@@ -23,11 +23,11 @@ class ComfyUIDeployExternalNumberSlider:
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
-53
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@@ -1,53 +0,0 @@
import re
class StringFunction:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"action": (["append", "replace"], {}),
"tidy_tags": (["yes", "no"], {}),
},
"optional": {
"text_a": ("STRING", {"multiline": True, "dynamicPrompts": False}),
"text_b": ("STRING", {"multiline": True, "dynamicPrompts": False}),
"text_c": ("STRING", {"multiline": True, "dynamicPrompts": False}),
},
}
RETURN_TYPES = ("STRING",)
FUNCTION = "exec"
CATEGORY = "utils"
OUTPUT_NODE = True
def exec(self, action, tidy_tags, text_a="", text_b="", text_c=""):
tidy_tags = tidy_tags == "yes"
out = ""
if action == "append":
out = (", " if tidy_tags else "").join(
filter(None, [text_a, text_b, text_c])
)
else:
if text_c is None:
text_c = ""
if text_b.startswith("/") and text_b.endswith("/"):
regex = text_b[1:-1]
out = re.sub(regex, text_c, text_a)
else:
out = text_a.replace(text_b, text_c)
if tidy_tags:
out = re.sub(r"\s{2,}", " ", out)
out = out.replace(" ,", ",")
out = re.sub(r",{2,}", ",", out)
out = out.strip()
return {"ui": {"text": (out,)}, "result": (out,)}
NODE_CLASS_MAPPINGS = {
"ComfyUIDeployStringCombine": StringFunction,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyUIDeployStringCombine": "String Combine (ComfyUI Deploy)",
}
+2 -2
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@@ -20,11 +20,11 @@ class ComfyUIDeployExternalText:
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
-46
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@@ -1,46 +0,0 @@
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
WILDCARD = AnyType("*")
class ComfyUIDeployExternalTextAny:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": "input_text"},
),
},
"optional": {
"default_value": (
"STRING",
{"multiline": True, "default": ""},
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
}
}
RETURN_TYPES = (WILDCARD,)
RETURN_NAMES = ("text",)
FUNCTION = "run"
CATEGORY = "text"
def run(self, input_id, default_value=None, display_name=None, description=None):
return [default_value]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextAny": ComfyUIDeployExternalTextAny}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextAny": "External Text Any (ComfyUI Deploy)"}
+52
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@@ -0,0 +1,52 @@
import folder_paths
from PIL import Image, ImageOps
import numpy as np
import torch
import json
class ComfyUIDeployExternalTextList:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": 'input_text_list'},
),
"text": (
"STRING",
{"multiline": True, "default": "[]"},
),
},
"optional": {
"display_name": (
"STRING",
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": "Description of the node (optional)"},
),
}
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("text",)
OUTPUT_IS_LIST = (True,)
FUNCTION = "run"
CATEGORY = "text"
def run(self, input_id, text=None, display_name=None, description=None):
text_list = []
try:
text_list = json.loads(text) # Assuming text is a JSON array string
except Exception as e:
print(f"Error processing images: {e}")
pass
return ([text_list],)
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextList": ComfyUIDeployExternalTextList}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextList": "External Text List (ComfyUI Deploy)"}
+4 -4
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@@ -764,14 +764,14 @@ class ComfyUIDeployExternalVideo:
"optional": {
"meta_batch": ("VHS_BatchManager",),
"vae": ("VAE",),
"default_video": (sorted(files),),
"default_value": (sorted(files),),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
{"multiline": False, "default": "Name of the node (optional)"},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "default": "Description of the node (optional)"},
),
},
"hidden": {
@@ -834,7 +834,7 @@ class ComfyUIDeployExternalVideo:
):
out_file.write(chunk)
else:
video = kwargs.get("default_video", None)
video = kwargs.get("default_value", "")
if video is None:
raise "No default video given and no external video provided"
video_path = folder_paths.get_annotated_filepath(video.strip('"'))
-60
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@@ -1,60 +0,0 @@
import folder_paths
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
from os import walk
WILDCARD = AnyType("*")
MODEL_EXTENSIONS = {
"safetensors": "SafeTensors file format",
"ckpt": "Checkpoint file",
"pth": "PyTorch serialized file",
"pkl": "Pickle file",
"onnx": "ONNX file",
}
def fetch_files(path):
for (dirpath, dirnames, filenames) in walk(path):
fs = []
if len(dirnames) > 0:
for dirname in dirnames:
fs.extend(fetch_files(f"{dirpath}/{dirname}"))
for filename in filenames:
# Remove "./models/" from the beginning of dirpath
relative_dirpath = dirpath.replace("./models/", "", 1)
file_path = f"{relative_dirpath}/{filename}"
# Only add files that are known model extensions
file_extension = filename.split('.')[-1].lower()
if file_extension in MODEL_EXTENSIONS:
fs.append(file_path)
return fs
allModels = fetch_files("./models")
class ComfyUIDeployModalList:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": (allModels, ),
}
}
RETURN_TYPES = (WILDCARD,)
RETURN_NAMES = ("model",)
FUNCTION = "run"
CATEGORY = "model"
def run(self, model=""):
# Split the model path by '/' and select the last item
model_name = model.split('/')[-1]
return [model_name]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployModelList": ComfyUIDeployModalList}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployModelList": "Model List (ComfyUI Deploy)"}
-100
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@@ -1,100 +0,0 @@
import os
import json
import numpy as np
from PIL import Image
from PIL.PngImagePlugin import PngInfo
import folder_paths
class ComfyDeployOutputImage:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
self.prefix_append = ""
self.compress_level = 4
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE", {"tooltip": "The images to save."}),
"filename_prefix": (
"STRING",
{
"default": "ComfyUI",
"tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
},
),
"file_type": (["png", "jpg", "webp"], {"default": "webp"}),
"quality": ("INT", {"default": 80, "min": 1, "max": 100, "step": 1}),
"output_id": (
"STRING",
{"multiline": False, "default": "output_images"},
),
},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
}
RETURN_TYPES = ()
FUNCTION = "run"
OUTPUT_NODE = True
CATEGORY = "output"
DESCRIPTION = "Saves the input images to your ComfyUI output directory."
def run(
self,
images,
filename_prefix="ComfyUI",
file_type="png",
quality=80,
output_id="output_images",
prompt=None,
extra_pnginfo=None,
):
filename_prefix += self.prefix_append
full_output_folder, filename, counter, subfolder, filename_prefix = (
folder_paths.get_save_image_path(
filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
)
)
results = list()
for batch_number, image in enumerate(images):
i = 255.0 * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
metadata = PngInfo()
if prompt is not None:
metadata.add_text("prompt", json.dumps(prompt))
if extra_pnginfo is not None:
for x in extra_pnginfo:
metadata.add_text(x, json.dumps(extra_pnginfo[x]))
filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
file = f"{filename_with_batch_num}_{counter:05}_.{file_type}"
file_path = os.path.join(full_output_folder, file)
if file_type == "png":
img.save(
file_path, pnginfo=metadata, compress_level=self.compress_level
)
elif file_type == "jpg":
img.save(file_path, quality=quality, optimize=True)
elif file_type == "webp":
img.save(file_path, quality=quality)
results.append(
{
"filename": file,
"subfolder": subfolder,
"type": self.type,
"output_id": output_id,
}
)
counter += 1
return {"ui": {"images": results}}
NODE_CLASS_MAPPINGS = {"ComfyDeployOutputImage": ComfyDeployOutputImage}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputImage": "Image Output (ComfyDeploy)"}
+373 -1760
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+17 -37
View File
@@ -6,12 +6,10 @@ from PIL import Image, ImageOps
from io import BytesIO
from pydantic import BaseModel as PydanticBaseModel
class BaseModel(PydanticBaseModel):
class Config:
arbitrary_types_allowed = True
class Status(Enum):
NOT_STARTED = "not-started"
RUNNING = "running"
@@ -19,7 +17,6 @@ class Status(Enum):
FAILED = "failed"
UPLOADING = "uploading"
class StreamingPrompt(BaseModel):
workflow_api: Any
auth_token: str
@@ -27,52 +24,42 @@ class StreamingPrompt(BaseModel):
running_prompt_ids: set[str] = set()
status_endpoint: Optional[str]
file_upload_endpoint: Optional[str]
workflow: Any
gpu_event_id: Optional[str] = None
class SimplePrompt(BaseModel):
status_endpoint: Optional[str]
file_upload_endpoint: Optional[str]
token: Optional[str]
workflow_api: dict
status: Status = Status.NOT_STARTED
progress: set = set()
last_updated_node: Optional[str] = None
last_updated_node: Optional[str] = None,
uploading_nodes: set = set()
done: bool = False
is_realtime: bool = False
start_time: Optional[float] = None
gpu_event_id: Optional[str] = None
is_realtime: bool = False,
start_time: Optional[float] = None,
sockets = dict()
prompt_metadata: dict[str, SimplePrompt] = {}
streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
class BinaryEventTypes:
PREVIEW_IMAGE = 1
UNENCODED_PREVIEW_IMAGE = 2
max_output_id_length = 24
async def send_image(image_data, sid=None, output_id: str = None):
async def send_image(image_data, sid=None, output_id:str = None):
max_length = max_output_id_length
output_id = output_id[:max_length]
padded_output_id = output_id.ljust(max_length, "\x00")
encoded_output_id = padded_output_id.encode("ascii", "replace")
padded_output_id = output_id.ljust(max_length, '\x00')
encoded_output_id = padded_output_id.encode('ascii', 'replace')
image_type = image_data[0]
image = image_data[1]
max_size = image_data[2]
quality = image_data[3]
if max_size is not None:
if hasattr(Image, "Resampling"):
if hasattr(Image, 'Resampling'):
resampling = Image.Resampling.BILINEAR
else:
resampling = Image.ANTIALIAS
@@ -96,23 +83,17 @@ async def send_image(image_data, sid=None, output_id: str = None):
position_after = bytesIO.tell()
bytes_written = position_after - position_before
print(f"Bytes written: {bytes_written}")
image.save(bytesIO, format=image_type, quality=quality, compress_level=1)
preview_bytes = bytesIO.getvalue()
await send_bytes(BinaryEventTypes.PREVIEW_IMAGE, preview_bytes, sid=sid)
async def send_socket_catch_exception(function, message):
try:
await function(message)
except (
aiohttp.ClientError,
aiohttp.ClientPayloadError,
ConnectionResetError,
) as err:
except (aiohttp.ClientError, aiohttp.ClientPayloadError, ConnectionResetError) as err:
print("send error:", err)
def encode_bytes(event, data):
if not isinstance(event, int):
raise RuntimeError(f"Binary event types must be integers, got {event}")
@@ -122,10 +103,9 @@ def encode_bytes(event, data):
message.extend(data)
return message
async def send_bytes(event, data, sid=None):
message = encode_bytes(event, data)
print("sending image to ", event, sid)
if sid is None:
@@ -133,4 +113,4 @@ async def send_bytes(event, data, sid=None):
for ws in _sockets:
await send_socket_catch_exception(ws.send_bytes, message)
elif sid in sockets:
await send_socket_catch_exception(sockets[sid].send_bytes, message)
await send_socket_catch_exception(sockets[sid].send_bytes, message)
+2 -2
View File
@@ -1,8 +1,8 @@
[project]
name = "comfyui-deploy"
description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
version = "1.1.0"
license = { file = "LICENSE" }
version = "1.0.0"
license = "LICENSE"
dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
[project.urls]
-1
View File
@@ -3,5 +3,4 @@ pydantic
opencv-python
imageio-ffmpeg
brotli
tabulate
# logfire
+4
View File
@@ -0,0 +1,4 @@
/** @typedef {import('../../../web/scripts/api.js').api} API*/
import { api as _api } from '../../scripts/api.js';
/** @type {API} */
export const api = _api;
+4
View File
@@ -0,0 +1,4 @@
/** @typedef {import('../../../web/scripts/app.js').ComfyApp} ComfyApp*/
import { app as _app } from '../../scripts/app.js';
/** @type {ComfyApp} */
export const app = _app;
+52 -884
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+18
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@@ -0,0 +1,18 @@
// /** @typedef {import('../../../web/scripts/api.js').api} API*/
// import { api as _api } from "../../scripts/api.js";
// /** @type {API} */
// export const api = _api;
/** @typedef {typeof import('../../../web/scripts/widgets.js').ComfyWidgets} Widgets*/
import { ComfyWidgets as _ComfyWidgets } from "../../scripts/widgets.js";
/**
* @type {Widgets}
*/
export const ComfyWidgets = _ComfyWidgets;
// import { LGraphNode as _LGraphNode } from "../../types/litegraph.js";
/** @typedef {typeof import('../../../web/types/litegraph.js').LGraphNode} LGraphNode*/
/** @type {LGraphNode}*/
export const LGraphNode = LiteGraph.LGraphNode;
-1
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@@ -6,5 +6,4 @@ export const customInputNodes: Record<string, string> = {
ComfyUIDeployExternalNumberInt: "integer",
ComfyUIDeployExternalLora: "string - (public lora download url)",
ComfyUIDeployExternalCheckpoint: "string - (public checkpoints download url)",
ComfyUIDeployExternalFaceModel: "string - (public face model download url)",
};