test gradio

app.py

@@ -1,29 +1,31 @@
 import gradio as gr
 import torch
-from diffusers import StableDiffusion3Pipeline, ControlNetModel, UniPCMultistepScheduler
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
 from huggingface_hub import login
 import os
 
-# Log in to Hugging Face with token from environment variables
+# Log in to Hugging Face with your token
 token = os.getenv("HF_TOKEN")
 login(token=token)
 
-# Model IDs for the base Stable Diffusion model and ControlNet variant
-model_id = "stabilityai/stable-diffusion-3.5-large-turbo"
-controlnet_id = "lllyasviel/control_v11p_sd15_inpaint"  # Adjust based on ControlNet needs
+# Model IDs for Stable Diffusion 1.5 and ControlNet
+model_id = "runwayml/stable-diffusion-v1-5"  # Compatible with ControlNet
+controlnet_id = "lllyasviel/control_v11p_sd15_inpaint"
 
-# Load ControlNet and Stable Diffusion models
-controlnet = ControlNetModel.from_pretrained(controlnet_id, torch_dtype=torch.bfloat16)
-pipe = StableDiffusion3Pipeline.from_pretrained(model_id, controlnet=controlnet, torch_dtype=torch.bfloat16)
+# Load the ControlNet model and Stable Diffusion pipeline
+controlnet = ControlNetModel.from_pretrained(controlnet_id, torch_dtype=torch.float16)
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    model_id, controlnet=controlnet, torch_dtype=torch.float16
+)
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
 pipe = pipe.to("cuda") if torch.cuda.is_available() else pipe
 
-# Gradio interface function
+# Define the Gradio interface function
 def generate_image(prompt, reference_image):
-    # Prepare the reference image
+    # Prepare the reference image for ControlNet
     reference_image = reference_image.convert("RGB").resize((512, 512))
 
-    # Generate the image using the pipeline with ControlNet
+    # Generate the image with ControlNet conditioning
     generated_image = pipe(
         prompt=prompt,
         image=reference_image,
@@ -41,8 +43,8 @@ interface = gr.Interface(
         gr.Image(type="pil", label="Reference Image (Style)")
     ],
     outputs="image",
-    title="Image Generation with Stable Diffusion 3.5 and ControlNet",
-    description="Generates an image based on a text prompt and style reference image using Stable Diffusion 3.5 and ControlNet."
+    title="Image Generation with Stable Diffusion 1.5 and ControlNet",
+    description="Generates an image based on a text prompt and a reference image using Stable Diffusion 1.5 with ControlNet."
 )
 
 # Launch the Gradio interface