Update app.py

app.py

@@ -124,7 +124,7 @@ def end_session(req: gr.Request):
 
 
 def preprocess_image(image: Image.Image, 
-                    prompt: str,
+                    prompt: str = "",
                     negative_prompt: str = "",
                     style_name: str = "",
                     num_steps: int = 25,
@@ -139,25 +139,25 @@ def preprocess_image(image: Image.Image,
     Returns:
         Image.Image: The preprocessed image.
     """
-    if prompt is not None:
         
-        width, height  = image['composite'].size
-        ratio = np.sqrt(1024. * 1024. / (width * height))
-        new_width, new_height = int(width * ratio), int(height * ratio)
-        image = image['composite'].resize((new_width, new_height))
+    width, height  = image['composite'].size
+    ratio = np.sqrt(1024. * 1024. / (width * height))
+    new_width, new_height = int(width * ratio), int(height * ratio)
+    image = image['composite'].resize((new_width, new_height))
 
-        prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
-        
-        image = pipe_control(
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            image=image,
-            num_inference_steps=num_steps,
-            controlnet_conditioning_scale=controlnet_conditioning_scale,
-            guidance_scale=guidance_scale,
-            width=new_width,
-            height=new_height).images[0]
-        print(type(image))
+    prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
+    
+    print(prompt, negative_prompt, style_name, num_steps, guidance_scale, controlnet_conditioning_scale)
+    image = pipe_control(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        image=image,
+        num_inference_steps=num_steps,
+        controlnet_conditioning_scale=controlnet_conditioning_scale,
+        guidance_scale=guidance_scale,
+        width=new_width,
+        height=new_height).images[0]
+    
         
     processed_image = pipeline.preprocess_image(image)
     return processed_image