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app.py

@@ -5,9 +5,7 @@ import logging
 import torch
 from PIL import Image
 from diffusers import DiffusionPipeline
-from diffusers.pipelines.flux.pipeline_flux_controlnet import FluxControlNetPipeline
-from diffusers.models.controlnet_flux import FluxControlNetModel, FluxMultiControlNetModel
-#from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
+from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
 from huggingface_hub import hf_hub_download, HfFileSystem, ModelCard, snapshot_download
 import copy
 import random
@@ -332,26 +330,20 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css) as app:
                 deselect_lora_button = gr.Button("Deselect LoRA", variant="secondary")
             with gr.Column(scale=4):
                 result = gr.Image(label="Generated Image", format="png", show_share_button=False)
-
+        model_name = gr.Dropdown(label="Base Model", info="You can enter a huggingface model repo_id to want to use.", choices=models, value=models[0], allow_custom_value=True)
         with gr.Row():
             with gr.Accordion("Advanced Settings", open=False):
                 with gr.Column():
-                    with gr.Row():
-                        model_name = gr.Dropdown(label="Base Model", info="You can enter a huggingface model repo_id to want to use.", choices=models, value=models[0], allow_custom_value=True)
-
                     with gr.Row():
                         cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, step=0.5, value=3.5)
                         steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=28)
-                    
                     with gr.Row():
                         width = gr.Slider(label="Width", minimum=256, maximum=1536, step=64, value=1024)
                         height = gr.Slider(label="Height", minimum=256, maximum=1536, step=64, value=1024)
-                    
                     with gr.Row():
                         randomize_seed = gr.Checkbox(True, label="Randomize seed")
                         seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, randomize=True)
                         lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, step=0.01, value=0.95)
-
                     with gr.Accordion("External LoRA", open=True):
                         with gr.Column():
                             lora_repo_json = gr.JSON(value=[{}] * num_loras, visible=False)
@@ -388,7 +380,6 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', fill_width=True, css=css) as app:
                                     lora_download = [None] * num_loras
                                     for i in range(num_loras):
                                         lora_download[i] = gr.Button(f"Get and set LoRA to {int(i+1)}")
-
                     with gr.Accordion("ControlNet", open=False):
                         with gr.Column():
                             cn_on = gr.Checkbox(False, label="Use ControlNet")

requirements.txt

@@ -11,4 +11,5 @@ timm
 einops
 controlnet-aux
 kornia
-numpy
+numpy
+opencv-python