no controlnet

app.py

@@ -6,6 +6,7 @@ import os
 from diffusers.pipelines.flux.pipeline_flux_controlnet_inpaint import (
     FluxControlNetInpaintPipeline,
 )
+from diffusers.pipelines.flux.pipeline_flux_inpaint import FluxInpaintPipeline
 from diffusers.models.controlnet_flux import FluxControlNetModel
 from controlnet_aux import CannyDetector
 import psutil
@@ -23,10 +24,11 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 base_model = "black-forest-labs/FLUX.1-dev"
 controlnet_model = "YishaoAI/flux-dev-controlnet-canny-kid-clothes"
 
-controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=dtype)
-pipe = FluxControlNetInpaintPipeline.from_pretrained(
-    base_model, controlnet=controlnet, torch_dtype=dtype
-).to(device)
+# controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=dtype)
+# pipe = FluxControlNetInpaintPipeline.from_pretrained(
+#     base_model, controlnet=controlnet, torch_dtype=dtype
+# ).to(device)
+pipe = FluxInpaintPipeline.from_pretrained(base_model, torch_dtype=dtype).to(device)
 
 pipe.enable_model_cpu_offload()
 
@@ -61,7 +63,7 @@ def inpaint(
         prompt,
         image=image,
         control_image=canny_image,
-        controlnet_conditioning_scale=controlnet_conditioning_scale,
+        # controlnet_conditioning_scale=controlnet_conditioning_scale,
         mask_image=mask,
         strength=strength,
         num_inference_steps=num_inference_steps,
@@ -94,7 +96,7 @@ with gr.Blocks() as demo:
         description="Upload an image and a mask, then provide a prompt to generate an inpainted image.",
     )
 
-demo.launch(debug=True, show_api=False, enable_queue=False)
+demo.launch(debug=True)
 
 # import gradio as gr
 # import numpy as np