Update app.py

app.py

@@ -33,13 +33,13 @@ pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, times
 from safety_checker import StableDiffusionSafetyChecker
 from transformers import CLIPFeatureExtractor
 
-safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker").to(device)
-feature_extractor = CLIPFeatureExtractor.from_pretrained("openai/clip-vit-base-patch32")
+#safety_checker = StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker").to(device)
+#feature_extractor = CLIPFeatureExtractor.from_pretrained("openai/clip-vit-base-patch32")
 
-def check_nsfw_images(images: list[Image.Image]) -> list[bool]:
-    safety_checker_input = feature_extractor(images, return_tensors="pt").to(device)
-    has_nsfw_concepts = safety_checker(images=[images], clip_input=safety_checker_input.pixel_values.to(device))
-    return has_nsfw_concepts
+#def check_nsfw_images(images: list[Image.Image]) -> list[bool]:
+#    safety_checker_input = feature_extractor(images, return_tensors="pt").to(device)
+#    has_nsfw_concepts = safety_checker(images=[images], clip_input=safety_checker_input.pixel_values.to(device))
+#    return has_nsfw_concepts
 
 # Function 
 @spaces.GPU(enable_queue=True)
@@ -72,10 +72,10 @@ def generate_image(prompt, base, motion, step, progress=gr.Progress()):
 
     output = pipe(prompt=prompt, guidance_scale=1.0, num_inference_steps=step, callback=progress_callback, callback_steps=1)
 
-    has_nsfw_concepts = check_nsfw_images([output.frames[0][0]])
-    if has_nsfw_concepts[0]:
-        gr.Warning("NSFW content detected.")
-        return None
+    #has_nsfw_concepts = check_nsfw_images([output.frames[0][0]])
+    #if has_nsfw_concepts[0]:
+    #    gr.Warning("NSFW content detected.")
+   #     return None
 
     name = str(uuid.uuid4()).replace("-", "")
     path = f"/tmp/{name}.mp4"