Update app.py

app.py

@@ -18,17 +18,17 @@ from diffusers.utils import export_to_gif, load_image
 from diffusers.models.modeling_utils import ModelMixin
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file, save_file
-from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler, StableDiffusionXLPipeline, UNet2DConditionModel, AutoencoderKL, UNet3DConditionModel
+from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, EulerDiscreteScheduler, DDIMScheduler, StableDiffusionXLPipeline, UNet2DConditionModel, AutoencoderKL, UNet3DConditionModel
 import jax
 import jax.numpy as jnp
 
 last_motion=None
 fps=15
-time=5
+time=2
 device = "cuda"
 dtype = torch.float16
 result=[]
-step = 2
+step = 30
 #repo = "ByteDance/AnimateDiff-Lightning"
 #ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
 #base = "emilianJR/epiCRealism"
@@ -142,18 +142,15 @@ def Piper(image,positive,negative,motion):
         last_motion = motion
 
     pipe.to(device)
-
-    if negative == "":
-        negative = None
-
+    
     return pipe(
-        positive,
+        prompt=positive,
         negative_prompt=negative,
         height=1024,
         width=576,
         ip_adapter_image=image.convert("RGB").resize((576,1024)),
         num_inference_steps=step,
-        guidance_scale=1,
+        guidance_scale=7.5,
         num_frames=(fps*time)
     )
 
@@ -194,12 +191,13 @@ def run(i,m,p1,p2,*result):
         return out
 
 pipe = AnimateDiffPipeline.from_pretrained(base, motion_adapter=adapter, torch_dtype=dtype).to(device)
-pipe.scheduler = EulerDiscreteScheduler(
-    beta_start=0.00085,
-    beta_end=0.012,
-    beta_schedule="linear",
-    timestep_spacing="trailing",
-    steps_offset=1
+pipe.scheduler = DDIMScheduler(
+        clip_sample=False,
+        beta_start=0.00085,
+        beta_end=0.012,
+        beta_schedule="linear",
+        timestep_spacing="trailing",
+        steps_offset=1
 )
 pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
 pipe.enable_vae_slicing()