Update app.py

app.py

@@ -49,6 +49,15 @@ def infer(
     if model_id is None:
         raise ValueError("Please specify the base model name or path")
 
+    params = {'prompt': prompt,
+              'negative_prompt': negative_prompt,
+              'guidance_scale': guidance_scale,
+              'num_inference_steps': num_inference_steps,
+              'width': width,
+              'height': height,
+              'generator': generator
+             }
+
     if controlnet_checkbox:
         if controlnet_mode == "depth_map":
             controlnet = ControlNetModel.from_pretrained(
@@ -84,8 +93,10 @@ def infer(
                                                                  controlnet=controlnet,
                                                                  torch_dtype=torch_dtype, 
                                                                  safety_checker=None).to(device)
-        controlnet_image = load_image(controlnet_image).convert('RGB')
-        print(type(controlnet_image))
+        params['control_image'] = controlnet_image
+        params['controlnet_conditioning_scale'] = controlnet_strength
+        # controlnet_image = load_image(controlnet_image).convert('RGB')
+        # print(type(controlnet_image))
     else:
         pipe = StableDiffusionPipeline.from_pretrained(model_id, 
                                                        torch_dtype=torch_dtype, 
@@ -95,7 +106,8 @@ def infer(
     if ip_adapter_checkbox:
         pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter-plus_sd15.bin")
         pipe.set_ip_adapter_scale(ip_adapter_scale)
-        ip_adapter_image = load_image(ip_adapter_image).convert('RGB') 
+        params['ip_adapter_image'] = ip_adapter_image
+        # ip_adapter_image = load_image(ip_adapter_image).convert('RGB') 
     
     pipe.unet = PeftModel.from_pretrained(pipe.unet, unet_sub_dir)
     pipe.text_encoder = PeftModel.from_pretrained(pipe.text_encoder, text_encoder_sub_dir)
@@ -109,32 +121,7 @@ def infer(
 
     pipe.to(device)
 
-    if controlnet_checkbox:
-        image = pipe(
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            guidance_scale=guidance_scale,
-            num_inference_steps=num_inference_steps,
-            width=width,
-            height=height,
-            generator=generator,
-            control_image=controlnet_image, 
-            controlnet_conditioning_scale=controlnet_strength,
-            ip_adapter_image=ip_adapter_image if ip_adapter_checkbox else None
-        ).images[0]
-    else:
-        image = pipe(
-            prompt=prompt,
-            negative_prompt=negative_prompt,
-            guidance_scale=guidance_scale,
-            num_inference_steps=num_inference_steps,
-            width=width,
-            height=height,
-            generator=generator,
-            ip_adapter_image=ip_adapter_image if ip_adapter_checkbox else None
-        ).images[0]
-    
-    return image
+    return pipe(**params).images[0]
 
 css = """
 #col-container {