Update app.py

app.py

@@ -62,21 +62,14 @@ def inference(prompt, guidance, steps, width=512, height=512, seed=0, img=None,
       return txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator), None
   except Exception as e:
     return None, error_str(e)
+      
+      def dummy(images, **kwargs): return result.images,False
 
-    def check_safety(x_image):
-#     safety_checker_input = safety_feature_extractor(numpy_to_pil(x_image), return_tensors="pt")
-    # x_checked_image, has_nsfw_concept = safety_checker(images=x_image, clip_input=safety_checker_input.pixel_values)
-#     x_checked_image = x_image
-    # assert x_checked_image.shape[0] == len(has_nsfw_concept)
-    # for i in range(len(has_nsfw_concept)):
-    #     if has_nsfw_concept[i]:
-    #         x_checked_image[i] = load_replacement(x_checked_image[i])
-    return x_image, False # has_nsfw_concept
-    
 def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator):
 
     result = pipe(
       prompt,
+      pipe.safety_checker = dummy,
       negative_prompt = neg_prompt,
       num_inference_steps = int(steps),
       guidance_scale = guidance,
@@ -92,7 +85,7 @@ def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height
     img = img.resize((int(img.width * ratio), int(img.height * ratio)), Image.LANCZOS)
     result = pipe_i2i(
         prompt,
-        check_safety = dummy,
+        pipe.safety_checker = dummy,
         negative_prompt = neg_prompt,
         init_image = img,
         num_inference_steps = int(steps),