Update app.py

app.py

@@ -25,8 +25,8 @@ from diffusers.utils import export_to_gif, load_image
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file, save_file
 from diffusers import StableDiffusionPipeline
-from diffusers import AnimateDiffSparseControlNetPipeline
-from diffusers.models import AutoencoderKL, MotionAdapter, SparseControlNetModel
+from diffusers import AnimateDiffPipeline
+from diffusers.models import AutoencoderKL, MotionAdapter
 from diffusers.schedulers import DPMSolverMultistepScheduler
 from PIL import Image, ImageDraw, ImageFont
 
@@ -52,8 +52,6 @@ else:
 
 #base = "emilianJR/epiCRealism"
 base = "SG161222/Realistic_Vision_V5.1_noVAE"
-controlnet_id = "guoyww/animatediff-sparsectrl-scribble"
-lora_adapter_id = "guoyww/animatediff-motion-lora-v1-5-3"
 vae_id = "stabilityai/sd-vae-ft-mse"
 motion_adapter = "guoyww/animatediff-motion-adapter-v1-5-3"
 
@@ -118,8 +116,8 @@ function custom(){
 image_pipe = StableDiffusionPipeline.from_pretrained(base, torch_dtype=dtype, safety_checker=None).to(device)
 
 adapter = MotionAdapter.from_pretrained(motion_adapter, torch_dtype=dtype, safety_checker=None).to(device)
-controlnet = SparseControlNetModel.from_pretrained(controlnet_id, torch_dtype=torch.float16).to(device)
 vae = AutoencoderKL.from_pretrained(vae_id, torch_dtype=torch.float16).to(device)
+
 scheduler = DPMSolverMultistepScheduler.from_pretrained(
     base,
     subfolder="scheduler",
@@ -127,16 +125,7 @@ scheduler = DPMSolverMultistepScheduler.from_pretrained(
     algorithm_type="dpmsolver++",
     use_karras_sigmas=True
 )
-pipe = AnimateDiffSparseControlNetPipeline.from_pretrained(
-    base,
-    motion_adapter=motion_adapter,
-    controlnet=controlnet,
-    vae=vae,
-    scheduler=scheduler,
-    torch_dtype=torch.float16
-).to(device)
-
-pipe.scheduler = DDIMScheduler.from_pretrained(
+scheduler2 = DDIMScheduler.from_pretrained(
     base,
     subfolder="scheduler",
     clip_sample=False,
@@ -144,6 +133,15 @@ pipe.scheduler = DDIMScheduler.from_pretrained(
     beta_schedule="linear",
     steps_offset=1,
 )
+
+pipe = AnimateDiffPipeline.from_pretrained(
+    base,
+    motion_adapter=motion_adapter,
+    vae=vae,
+    scheduler=scheduler,
+    torch_dtype=torch.float16
+).to(device)
+
 pipe.enable_vae_slicing()
 pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
 pipe.enable_model_cpu_offload()