Update app.py

app.py

@@ -125,7 +125,7 @@ et = time.time()
 elapsed_time = et - st
 print('Loading ControlNet took: ', elapsed_time, 'seconds')
 st = time.time()
-vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
+vae = AutoencoderKL.from_pretrained("nubby/blessed-sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 et = time.time()
 elapsed_time = et - st
 print('Loading VAE took: ', elapsed_time, 'seconds')
@@ -137,7 +137,7 @@ st = time.time()
 #                                                                 controlnet=[identitynet, zoedepthnet],
 #                                                                 torch_dtype=torch.float16)
 
-pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("SG161222/RealVisXL_V5.0", 
+pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("SG161222/RealVisXL_V4.0", 
                                                                 vae=vae,
                                                                 controlnet=[identitynet, zoedepthnet],
                                                                 torch_dtype=torch.float16)
@@ -261,6 +261,7 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_stre
         face_emb = face_info['embedding']
         face_kps = draw_kps(face_image, face_info['kps'])
     except:
+        face_info = None
         face_detected = False
         face_emb = None
         face_kps = face_image
@@ -316,7 +317,7 @@ def run_lora(face_image, prompt, negative, lora_scale, selected_state, face_stre
 run_lora.zerogpu = True
 
 
-@spaces.GPU(duration=100)
+@spaces.GPU(duration=75)
 def generate_image(prompt, negative, face_emb, face_image, face_kps, image_strength, guidance_scale, face_strength, depth_control_scale, repo_name, loaded_state_dict, lora_scale, sdxl_loras, selected_state_index, face_detected, st):
     global last_fused, last_lora