Update app.py

app.py

@@ -132,15 +132,15 @@ print('Loading VAE took: ', elapsed_time, 'seconds')
 st = time.time()
 
 #pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("stablediffusionapi/albedobase-xl-v21",
-pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("frankjoshua/albedobaseXL_v21",
-                                                                 vae=vae,
-                                                                 controlnet=[identitynet, zoedepthnet],
-                                                                 torch_dtype=torch.float16)
+#pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("frankjoshua/albedobaseXL_v21",
+#                                                                 vae=vae,
+#                                                                 controlnet=[identitynet, zoedepthnet],
+#                                                                 torch_dtype=torch.float16)
 
-#pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("SG161222/RealVisXL_V5.0", 
-#                                                                vae=vae,
-#                                                                controlnet=[identitynet, zoedepthnet],
-#                                                                torch_dtype=torch.float16)
+pipe = StableDiffusionXLInstantIDImg2ImgPipeline.from_pretrained("SG161222/RealVisXL_V5.0", 
+                                                                vae=vae,
+                                                                controlnet=[identitynet, zoedepthnet],
+                                                                torch_dtype=torch.float16)
 
 pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True)
 pipe.load_ip_adapter_instantid(face_adapter)
@@ -374,7 +374,7 @@ def generate_image(prompt, negative, face_emb, face_image, face_kps, image_stren
         image=face_image,
         strength=1-image_strength,
         control_image=control_images,
-        num_inference_steps=30,
+        num_inference_steps=36,
         guidance_scale=guidance_scale,
         controlnet_conditioning_scale=control_scales,
     ).images[0]