Update app.py

app.py

@@ -114,8 +114,8 @@ def predict(dict, prompt="", negative_prompt = default_negative_prompt, guidance
         negative_prompt = None
 
     
-    init_image = dict["image"].convert("RGB").resize((1024, 1024))
-    mask = dict["mask"].convert("L").resize((1024, 1024))
+    # init_image = dict["image"].convert("RGB").resize((1024, 1024))
+    # mask = dict["mask"].convert("L").resize((1024, 1024))
 
     width, height = get_size(init_image)
 
@@ -160,23 +160,13 @@ def predict(dict, prompt="", negative_prompt = default_negative_prompt, guidance
                   negative_prompt=negative_prompt,
                   image = masked_image, # control image V
                   init_image = init_image,
-                  mask_image=mask_tensor,
-                  guidance_scale=guidance_scale,
+                  mask_image = mask_tensor,
+                  guidance_scale = guidance_scale,
                   num_inference_steps=int(steps),
-                  # strength=strength,
+                  strength=strength,
                   generator=generator,
                   controlnet_conditioning_sale=1.0)
 
-    # gen_img = pipe(negative_prompt=default_negative_prompt, prompt=prompt, 
-    #         controlnet_conditioning_sale=1.0, 
-    #         num_inference_steps=12, 
-    #         height=height, width=width, 
-    #         image = masked_image, # control image
-    #         init_image = init_image,     
-    #         mask_image = mask_tensor,
-    #         guidance_scale = 1.2,
-    #         generator=generator).images[0]
-
     torch.cuda.empty_cache
     return output.images[0] #, gr.update(visible=True)