Update app.py

app.py

@@ -73,6 +73,7 @@ else:
     # )
 
 # t2i_pipe.load_lora_weights("wanghuging/skin_demo", weight_name="skin_demo.safetensors")
+t2i_pipe.safety_checker = lambda images, clip_input: (images, False)
 t2i_pipe.to(device=torch_device, dtype=torch_dtype).to(device)
 t2i_pipe.set_progress_bar_config(disable=True)
 i2i_pipe.to(device=torch_device, dtype=torch_dtype).to(device)
@@ -120,14 +121,14 @@ async def predict(init_image, prompt, strength, steps, seed=1231231):
             output_type="pil",
         )
     print(f"Pipe took {time.time() - last_time} seconds")
-    nsfw_content_detected = (
-        results.nsfw_content_detected[0]
-        if "nsfw_content_detected" in results
-        else False
-    )
-    if nsfw_content_detected:
-        gr.Warning("NSFW content detected.")
-        return Image.new("RGB", (512, 512))
+    # nsfw_content_detected = (
+    #     results.nsfw_content_detected[0]
+    #     if "nsfw_content_detected" in results
+    #     else False
+    # )
+    # if nsfw_content_detected:
+    #     gr.Warning("NSFW content detected.")
+    #     return Image.new("RGB", (512, 512))
     return results.images[0]