Please provide the file changes for which you want a commit message.

app.py

@@ -202,35 +202,6 @@ ADAPTER_SPECS = {
 
 LOADED_ADAPTERS = set()
 
-def update_dimensions_on_upload(image):
-    if image is None:
-        return 1024, 1024
-    
-    original_width, original_height = image.size
-    
-    if original_width > original_height:
-        new_width = 1024
-        aspect_ratio = original_height / original_width
-        new_height = int(new_width * aspect_ratio)
-    else:
-        new_height = 1024
-        aspect_ratio = original_width / original_height
-        new_width = int(new_height * aspect_ratio)
-        
-    new_width = (new_width // 8) * 8
-    new_height = (new_height // 8) * 8
-    
-    return new_width, new_height
-
-def update_lora(lora_adapter):
-    spec = ADAPTER_SPECS.get(lora_adapter)
-    if not spec:
-        raise gr.Error(f"Configuration not found for: {lora_adapter}")
-
-    adapter_name = spec["adapter_name"]
-    prompt = spec['prompt']
-    return prompt
-
 
 @spaces.GPU(duration=20)
 def infer(
@@ -242,6 +213,8 @@ def infer(
     randomize_seed,
     guidance_scale,
     steps,
+    width,
+    height,
     progress=gr.Progress(track_tqdm=True)
 ):
     gc.collect()
@@ -299,7 +272,8 @@ def infer(
 
     generator = torch.Generator(device=device).manual_seed(seed)
 
-    width, height = update_dimensions_on_upload(pil_images[0])
+    if height == 256 and width == 256:
+        height, width = None, None
 
     try:
         result_image = pipe(
@@ -334,11 +308,14 @@ def infer_example(images, prompt, lora_adapter):
     result, seed = infer(
         images=images_list,
         prompt=prompt,
+        negative_prompt="", # Default negative prompt for examples
         lora_adapter=lora_adapter,
         seed=0,
         randomize_seed=True,
         guidance_scale=1.0,
-        steps=4
+        steps=4,
+        width=None,
+        height=None
     )
     return result, seed
 
@@ -362,7 +339,7 @@ with gr.Blocks() as demo:
                     type="filepath", 
                     columns=2, 
                     rows=1, 
-                    height=300,
+                    # height=300, # Removed to prevent visual cropping
                     allow_preview=True
                 )
 
@@ -385,7 +362,7 @@ with gr.Blocks() as demo:
                 run_button = gr.Button("Edit Image", variant="primary")
 
             with gr.Column():
-                output_image = gr.Image(label="Output Image", interactive=False, format="png", height=363)
+                output_image = gr.Image(label="Output Image", interactive=False, format="png") # Removed height=363
                 
                 with gr.Row():
                     lora_adapter = gr.Dropdown(
@@ -399,6 +376,20 @@ with gr.Blocks() as demo:
                     randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
                     guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, step=0.1, value=1.0)
                     steps = gr.Slider(label="Inference Steps", minimum=1, maximum=50, step=1, value=4)
+                    width = gr.Slider(
+                        label="Width",
+                        minimum=256,
+                        maximum=2048,
+                        step=8,
+                        value=None,
+                    )
+                    height = gr.Slider(
+                        label="Height",
+                        minimum=256,
+                        maximum=2048,
+                        step=8,
+                        value=None,
+                    )
         
         gr.Examples(
             examples=[
@@ -427,7 +418,7 @@ with gr.Blocks() as demo:
     
     run_button.click(
         fn=infer,
-        inputs=[images, prompt, negative_prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps],
+        inputs=[images, prompt, negative_prompt, lora_adapter, seed, randomize_seed, guidance_scale, steps, width, height],
         outputs=[output_image, seed]
     )