diff --git a/src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py b/src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py
index f23c2d36dd..9fb2be02ac 100644
--- a/src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py
+++ b/src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py
@@ -341,21 +341,20 @@ class StableDiffusionPipelineSafe(DiffusionPipeline):
 
     def run_safety_checker(self, image, device, dtype, enable_safety_guidance):
         if self.safety_checker is not None:
+            images = image.copy()
             safety_checker_input = self.feature_extractor(self.numpy_to_pil(image), return_tensors="pt").to(device)
             image, has_nsfw_concept = self.safety_checker(
                 images=image, clip_input=safety_checker_input.pixel_values.to(dtype)
             )
-            flagged_images = None
+            flagged_images = np.zeros((2, *image.shape[1:]))
             if any(has_nsfw_concept):
                 logger.warning(
-                    "Potential NSFW content was detected in one or more images. A black image will be returned"
-                    " instead."
-                    f" {'You may look at this images in the `unsafe_images` variable of the output at your own discretion.' if enable_safety_guidance else 'Try again with a different prompt and/or seed.'} "
+                    "Potential NSFW content was detected in one or more images. A black image will be returned instead."
+                    f"{'You may look at this images in the `unsafe_images` variable of the output at your own discretion.' if enable_safety_guidance else 'Try again with a different prompt and/or seed.'}"
                 )
-                flagged_images = np.zeros((2, *image.shape[1:]))
                 for idx, has_nsfw_concept in enumerate(has_nsfw_concept):
                     if has_nsfw_concept:
-                        flagged_images[idx] = image[idx]
+                        flagged_images[idx] = images[idx]
                         image[idx] = np.zeros(image[idx].shape)  # black image
         else:
             has_nsfw_concept = None