Update app.py

app.py

@@ -9,8 +9,8 @@ import shutil
 from gradio_client import Client, handle_file
 
 # Function to load Stable Diffusion Inpainting model
-def load_inpainting_model():
-    model_path = "uberRealisticPornMerge_v13Inpainting.safetensors"
+def load_inpainting_model(model_name):
+    model_path = model_name
     device = "cuda" if torch.cuda.is_available() else "cpu"
     pipe = StableDiffusionInpaintPipeline.from_single_file(
         model_path,
@@ -60,8 +60,8 @@ def inpaint_image(input_image, mask_image, inpaint_pipeline):
     inpainted_image = upscale_image(inpainted_image)
     return inpainted_image
 
-# Function to process input image and mask
-def process_image(input_image):
+# Function to process input image and mask with the selected model
+def process_image(input_image, model_choice):
     # Save the input image temporarily to process with Replicate
     input_image_path = "temp_input_image.png"
     input_image.save(input_image_path)
@@ -73,8 +73,8 @@ def process_image(input_image):
     mask_image_path = "generated_mask.png"
     save_mask(mask_local_path, save_path=mask_image_path)
 
-    # Step 3: Load the inpainting model
-    inpaint_pipeline = load_inpainting_model()
+    # Step 3: Load the selected inpainting model
+    inpaint_pipeline = load_inpainting_model(model_choice)
 
     # Step 4: Open the mask image and perform inpainting
     mask_image = Image.open(mask_image_path)
@@ -94,12 +94,22 @@ with gr.Blocks() as demo:
         input_image = gr.Image(label="Upload Input Image", type="pil")
         output_image = gr.Image(type="pil", label="Output Image")
 
+    # Dropdown for selecting the model checkpoint
+    model_choice = gr.Dropdown(
+        choices=[
+            "uberRealisticPornMerge_v13Inpainting.safetensors", 
+            "realvisxlV50_v50LightningBakedvae.safetensors"
+        ],
+        label="Choose Inpainting Model",
+        value="uberRealisticPornMerge_v13Inpainting.safetensors"  # Default model
+    )
+
     # Button to trigger the process
     with gr.Row():
         btn = gr.Button("Run Inpainting")
 
     # Function to run when button is clicked
-    btn.click(fn=process_image, inputs=input_image, outputs=output_image)
+    btn.click(fn=process_image, inputs=[input_image, model_choice], outputs=output_image)
 
 # Launch the Gradio app with share=True to allow public access
 demo.launch(share=True)