Update app.py

app.py

@@ -28,6 +28,7 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
 )
 pipe.to("cuda")
 
+generator = torch.Generator(device="cuda")
 
 #pipe.enable_model_cpu_offload()
 
@@ -51,6 +52,8 @@ def infer(model_name, image_in, prompt, controlnet_conditioning_scale, guidance_
     image = Image.fromarray(image)
 
     lora_scale= 0.9
+
+    
     
     images = pipe(
         prompt, 
@@ -59,7 +62,7 @@ def infer(model_name, image_in, prompt, controlnet_conditioning_scale, guidance_
         controlnet_conditioning_scale=controlnet_conditioning_scale,
         guidance_scale = guidance_scale,
         num_inference_steps=50,
-        seed=seed,
+        generator=generator.manual_seed(seed),
         cross_attention_kwargs={"scale": lora_scale}
         ).images