在 Hugging Face Spaces 上使用 Gradio 免费运行 ComfyUI 工作流 - IT评测·应用市场-qidao123.com

import os
import random
import sys
from typing import Sequence, Mapping, Any, Union
import torch
+ import gradio as gr

复制代码

if __name__ == "__main__":
# 在导出的 Python 代码中注释掉对 main() 函数的调用
# 开启 Gradio 程序
with gr.Blocks() as app:
# 添加标题
gr.Markdown("# FLUX Style Shaping")
with gr.Row():
with gr.Column():
# 添加输入
prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
# 添加一个“Row”以将组并排显示
with gr.Row():
# 第一组包括结构图像和深度强度
with gr.Group():
structure_image = gr.Image(label="Structure Image", type="filepath")
depth_strength = gr.Slider(minimum=0, maximum=50, value=15, label="Depth Strength")
# 第二组包括风格图像和风格强度
with gr.Group():
style_image = gr.Image(label="Style Image", type="filepath")
style_strength = gr.Slider(minimum=0, maximum=1, value=0.5, label="Style Strength")
# 生成按钮
generate_btn = gr.Button("Generate")
with gr.Column():
# 输出图像
output_image = gr.Image(label="Generated Image")
# 当点击按钮时，它将触发“generate_image”函数，该函数带有相应的输入
# 并且输出是一张图像
generate_btn.click(
fn=generate_image,
inputs=[prompt_input, structure_image, style_image, depth_strength, style_strength],
outputs=[output_image]
)
app.launch(share=True)

复制代码

- def main():
+ def generate_image(prompt, structure_image, style_image, depth_strength, style_strength)

复制代码

loadimage_429 = loadimage.load_image(
- image="7038548d-d204-4810-bb74-d1dea277200a.png"
+ image=structure_image
)
# ...
loadimage_440 = loadimage.load_image(
- image="2013_CKS_01180_0005_000(the_court_of_pir_budaq_shiraz_iran_circa_1455-60074106).jpg"
+ image=style_image
)
# ...
fluxguidance_430 = fluxguidance.append(
- guidance=15,
+ guidance=depth_strength,
conditioning=get_value_at_index(cliptextencode_174, 0)
)
# ...
stylemodelapplyadvanced_442 = stylemodelapplyadvanced.apply_stylemodel(
- strength=0.5,
+ strength=style_strength,
conditioning=get_value_at_index(instructpixtopixconditioning_431, 0),
style_model=get_value_at_index(stylemodelloader_441, 0),
clip_vision_output=get_value_at_index(clipvisionencode_439, 0),
)
# ...
cliptextencode_174 = cliptextencode.encode(
- text="a girl looking at a house on fire",
+ text=prompt,
clip=get_value_at_index(cr_clip_input_switch_319, 0),
)

复制代码

saveimage_327 = saveimage.save_images(
filename_prefix=get_value_at_index(cr_text_456, 0),
images=get_value_at_index(vaedecode_321, 0),
)
+ saved_path = f"output/{saveimage_327['ui']['images'][0]['filename']}"
+ return saved_path

复制代码

python app.py

复制代码

* Running on local URL: http://127.0.0.1:7860
* Running on public URL: https://366fdd17b8a9072899.gradio.live

复制代码

from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="black-forest-labs/FLUX.1-Redux-dev", filename="flux1-redux-dev.safetensors", local_dir="models/style_models")
hf_hub_download(repo_id="black-forest-labs/FLUX.1-Depth-dev", filename="flux1-depth-dev.safetensors", local_dir="models/diffusion_models")
hf_hub_download(repo_id="Comfy-Org/sigclip_vision_384", filename="sigclip_vision_patch14_384.safetensors", local_dir="models/clip_vision")
hf_hub_download(repo_id="Kijai/DepthAnythingV2-safetensors", filename="depth_anything_v2_vitl_fp32.safetensors", local_dir="models/depthanything")
hf_hub_download(repo_id="black-forest-labs/FLUX.1-dev", filename="ae.safetensors", local_dir="models/vae/FLUX1")
hf_hub_download(repo_id="comfyanonymous/flux_text_encoders", filename="clip_l.safetensors", local_dir="models/text_encoders")
hf_hub_download(repo_id="comfyanonymous/flux_text_encoders", filename="t5xxl_fp16.safetensors", local_dir="models/text_encoders/t5")

复制代码

import gradio as gr
from huggingface_hub import hf_hub_download
+ import spaces
# ...
+ @spaces.GPU(duration=60) #modify the duration for the average it takes for your worflow to run, in seconds
def generate_image(prompt, structure_image, style_image, depth_strength, style_strength):

复制代码

@@ -4,6 +4,7 @@
from typing import Sequence, Mapping, Any, Union
import torch
import gradio as gr
from huggingface_hub import hf_hub_download
+from comfy import model_management
import spaces
hf_hub_download(repo_id="black-forest-labs/FLUX.1-Redux-dev", filename="flux1-redux-dev.safetensors", local_dir="models/style_models")
@@ -109,6 +110,62 @@
from nodes import NODE_CLASS_MAPPINGS
+intconstant = NODE_CLASS_MAPPINGS["INTConstant"]()
+dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()
+dualcliploader_357 = dualcliploader.load_clip(
+ clip_name1="t5/t5xxl_fp16.safetensors",
+ clip_name2="clip_l.safetensors",
+ type="flux",
+)
+cr_clip_input_switch = NODE_CLASS_MAPPINGS["CR Clip Input Switch"]()
+cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
+loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
+getimagesizeandcount = NODE_CLASS_MAPPINGS["GetImageSizeAndCount"]()
+vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]()
+vaeloader_359 = vaeloader.load_vae(vae_name="FLUX1/ae.safetensors")
+vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
+unetloader = NODE_CLASS_MAPPINGS["UNETLoader"]()
+unetloader_358 = unetloader.load_unet(
+ unet_name="flux1-depth-dev.safetensors", weight_dtype="default"
+)
+ksamplerselect = NODE_CLASS_MAPPINGS["KSamplerSelect"]()
+randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
+fluxguidance = NODE_CLASS_MAPPINGS["FluxGuidance"]()
+depthanything_v2 = NODE_CLASS_MAPPINGS["DepthAnything_V2"]()
+downloadandloaddepthanythingv2model = NODE_CLASS_MAPPINGS[
+ "DownloadAndLoadDepthAnythingV2Model"
+]()
+downloadandloaddepthanythingv2model_437 = (
+ downloadandloaddepthanythingv2model.loadmodel(
+ model="depth_anything_v2_vitl_fp32.safetensors"
+ )
+)
+instructpixtopixconditioning = NODE_CLASS_MAPPINGS[
+ "InstructPixToPixConditioning"
+]()
+text_multiline_454 = text_multiline.text_multiline(text="FLUX_Redux")
+clipvisionloader = NODE_CLASS_MAPPINGS["CLIPVisionLoader"]()
+clipvisionloader_438 = clipvisionloader.load_clip(
+ clip_name="sigclip_vision_patch14_384.safetensors"
+)
+clipvisionencode = NODE_CLASS_MAPPINGS["CLIPVisionEncode"]()
+stylemodelloader = NODE_CLASS_MAPPINGS["StyleModelLoader"]()
+stylemodelloader_441 = stylemodelloader.load_style_model(
+ style_model_name="flux1-redux-dev.safetensors"
+)
+text_multiline = NODE_CLASS_MAPPINGS["Text Multiline"]()
+emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
+cr_conditioning_input_switch = NODE_CLASS_MAPPINGS[
+ "CR Conditioning Input Switch"
+]()
+cr_model_input_switch = NODE_CLASS_MAPPINGS["CR Model Input Switch"]()
+stylemodelapplyadvanced = NODE_CLASS_MAPPINGS["StyleModelApplyAdvanced"]()
+basicguider = NODE_CLASS_MAPPINGS["BasicGuider"]()
+basicscheduler = NODE_CLASS_MAPPINGS["BasicScheduler"]()
+samplercustomadvanced = NODE_CLASS_MAPPINGS["SamplerCustomAdvanced"]()
+vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
+saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
+imagecrop = NODE_CLASS_MAPPINGS["ImageCrop+"]()
@@ -117,75 +174,6 @@
def generate_image(prompt, structure_image, style_image, depth_strength, style_strength):
import_custom_nodes()
with torch.inference_mode():
- intconstant = NODE_CLASS_MAPPINGS["INTConstant"]()
intconstant_83 = intconstant.get_value(value=1024)
intconstant_84 = intconstant.get_value(value=1024)
- dualcliploader = NODE_CLASS_MAPPINGS["DualCLIPLoader"]()
- dualcliploader_357 = dualcliploader.load_clip(
- clip_name1="t5/t5xxl_fp16.safetensors",
- clip_name2="clip_l.safetensors",
- type="flux",
- )
-
- cr_clip_input_switch = NODE_CLASS_MAPPINGS["CR Clip Input Switch"]()
cr_clip_input_switch_319 = cr_clip_input_switch.switch(
Input=1,
clip1=get_value_at_index(dualcliploader_357, 0),
clip2=get_value_at_index(dualcliploader_357, 0),
)
- cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
cliptextencode_174 = cliptextencode.encode(
text=prompt,
clip=get_value_at_index(cr_clip_input_switch_319, 0),
)
cliptextencode_175 = cliptextencode.encode(
text="purple", clip=get_value_at_index(cr_clip_input_switch_319, 0)
)
- loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
loadimage_429 = loadimage.load_image(image=structure_image)
- imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
imageresize_72 = imageresize.execute(
width=get_value_at_index(intconstant_83, 0),
height=get_value_at_index(intconstant_84, 0),
interpolation="bicubic",
method="keep proportion",
condition="always",
multiple_of=16,
image=get_value_at_index(loadimage_429, 0),
)
- getimagesizeandcount = NODE_CLASS_MAPPINGS["GetImageSizeAndCount"]()
getimagesizeandcount_360 = getimagesizeandcount.getsize(
image=get_value_at_index(imageresize_72, 0)
)
- vaeloader = NODE_CLASS_MAPPINGS["VAELoader"]()
- vaeloader_359 = vaeloader.load_vae(vae_name="FLUX1/ae.safetensors")
- vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
vaeencode_197 = vaeencode.encode(
pixels=get_value_at_index(getimagesizeandcount_360, 0),
vae=get_value_at_index(vaeloader_359, 0),
)
- unetloader = NODE_CLASS_MAPPINGS["UNETLoader"]()
- unetloader_358 = unetloader.load_unet(
- unet_name="flux1-depth-dev.safetensors", weight_dtype="default"
- )
- ksamplerselect = NODE_CLASS_MAPPINGS["KSamplerSelect"]()
ksamplerselect_363 = ksamplerselect.get_sampler(sampler_name="euler")
- randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
randomnoise_365 = randomnoise.get_noise(noise_seed=random.randint(1, 2**64))
- fluxguidance = NODE_CLASS_MAPPINGS["FluxGuidance"]()
fluxguidance_430 = fluxguidance.append(
guidance=15, conditioning=get_value_at_index(cliptextencode_174, 0)
)
- downloadandloaddepthanythingv2model = NODE_CLASS_MAPPINGS[
- "DownloadAndLoadDepthAnythingV2Model"
- ]()
- downloadandloaddepthanythingv2model_437 = (
- downloadandloaddepthanythingv2model.loadmodel(
- model="depth_anything_v2_vitl_fp32.safetensors"
- )
- )
- depthanything_v2 = NODE_CLASS_MAPPINGS["DepthAnything_V2"]()
depthanything_v2_436 = depthanything_v2.process(
da_model=get_value_at_index(downloadandloaddepthanythingv2model_437, 0),
images=get_value_at_index(getimagesizeandcount_360, 0),
)
- instructpixtopixconditioning = NODE_CLASS_MAPPINGS[
- "InstructPixToPixConditioning"
- ]()
instructpixtopixconditioning_431 = instructpixtopixconditioning.encode(
positive=get_value_at_index(fluxguidance_430, 0),
negative=get_value_at_index(cliptextencode_175, 0),
vae=get_value_at_index(vaeloader_359, 0),
pixels=get_value_at_index(depthanything_v2_436, 0),
)
- clipvisionloader = NODE_CLASS_MAPPINGS["CLIPVisionLoader"]()
- clipvisionloader_438 = clipvisionloader.load_clip(
- clip_name="sigclip_vision_patch14_384.safetensors"
- )
loadimage_440 = loadimage.load_image(image=style_image)
- clipvisionencode = NODE_CLASS_MAPPINGS["CLIPVisionEncode"]()
clipvisionencode_439 = clipvisionencode.encode(
crop="center",
clip_vision=get_value_at_index(clipvisionloader_438, 0),
image=get_value_at_index(loadimage_440, 0),
)
- stylemodelloader = NODE_CLASS_MAPPINGS["StyleModelLoader"]()
- stylemodelloader_441 = stylemodelloader.load_style_model(
- style_model_name="flux1-redux-dev.safetensors"
- )
-
- text_multiline = NODE_CLASS_MAPPINGS["Text Multiline"]()
text_multiline_454 = text_multiline.text_multiline(text="FLUX_Redux")
- emptylatentimage = NODE_CLASS_MAPPINGS["EmptyLatentImage"]()
- cr_conditioning_input_switch = NODE_CLASS_MAPPINGS[
- "CR Conditioning Input Switch"
- ]()
- cr_model_input_switch = NODE_CLASS_MAPPINGS["CR Model Input Switch"]()
- stylemodelapplyadvanced = NODE_CLASS_MAPPINGS["StyleModelApplyAdvanced"]()
- basicguider = NODE_CLASS_MAPPINGS["BasicGuider"]()
- basicscheduler = NODE_CLASS_MAPPINGS["BasicScheduler"]()
- samplercustomadvanced = NODE_CLASS_MAPPINGS["SamplerCustomAdvanced"]()
- vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
- saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
- imagecrop = NODE_CLASS_MAPPINGS["ImageCrop+"]()
emptylatentimage_10 = emptylatentimage.generate(
width=get_value_at_index(imageresize_72, 1),
height=get_value_at_index(imageresize_72, 2),
batch_size=1,
)

复制代码

from comfy import model_management
# 添加所有加载 safetensors 文件的模型
model_loaders = [dualcliploader_357, vaeloader_359, unetloader_358, clipvisionloader_438, stylemodelloader_441, downloadandloaddepthanythingv2model_437]
# 检查哪些模型是有效的，并确定最佳加载方式
valid_models = [
getattr(loader[0], 'patcher', loader[0])
for loader in model_loaders
if not isinstance(loader[0], dict) and not isinstance(getattr(loader[0], 'patcher', None), dict)
]
# 最终加载模型
model_management.load_models_gpu(valid_models)

复制代码