Update app.py

app.py

@@ -42,13 +42,15 @@ pipe = pipe.to(device)
 
 # Define the inference function
 @spaces.GPU
-def ghibli_transform(input_image, prompt="GHBLI anime style photo", strength=0.75, guidance_scale=7.5, num_steps=50):
+def ghibli_transform(input_image, prompt="GHBLI anime style photo", guidance_scale=3.5, num_steps=30):
+    print('canshu_guidance_scale',guidance_scale)
+    print('canshu_num_steps',num_steps)
     if input_image is None:
         raise gr.Error("No image uploaded! Please upload an image before clicking Transform.")
     
     # Process the input image (keep it as PIL Image)
     try:
-        init_image = input_image.convert("RGB").resize((768, 768))
+        init_image = input_image.convert("RGB").resize((1024, 768))
     except Exception as e:
         raise gr.Error(f"Failed to process image: {str(e)}")
     
@@ -61,10 +63,9 @@ def ghibli_transform(input_image, prompt="GHBLI anime style photo", strength=0.7
             # guidance_scale=guidance_scale,
             # num_inference_steps=num_steps  # Use the UI-provided value
             ######
-            guidance_scale=3.5,
-            num_inference_steps=30,
-            width=1024,
-            height=768
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_steps
+            
             ######
         ).images[0]
     except Exception as e:
@@ -81,9 +82,9 @@ with gr.Blocks(title="Ghibli Diffusion Image Transformer") as demo:
         with gr.Column():
             input_img = gr.Image(label="Upload Image", type="pil")
             prompt = gr.Textbox(label="Prompt", value="GHBLI anime style photo")
-            strength = gr.Slider(0, 1, value=0.75, step=0.05, label="Strength (How much to transform)")
-            guidance = gr.Slider(1, 20, value=7.5, step=0.5, label="Guidance Scale")
-            num_steps = gr.Slider(10, 100, value=50, step=5, label="Inference Steps (Higher = Better Quality, Slower)")
+           
+            guidance = gr.Slider(1, 20, value=3.5, step=0.5, label="Guidance Scale")
+            num_steps = gr.Slider(10, 100, value=30, step=5, label="Inference Steps (Higher = Better Quality, Slower)")
             submit_btn = gr.Button("Transform")
         with gr.Column():
             output_img = gr.Image(label="Ghibli-Style Output")