Update app.py

app.py

@@ -23,18 +23,18 @@ import jax
 import jax.numpy as jnp
 
 last_motion=None
-fps=15
-time=1
+fps=25
+time=5
 device = "cuda"
 dtype = torch.float16
 result=[]
 step = 2
 repo = "ByteDance/AnimateDiff-Lightning"
 ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
-base = "emilianJR/epiCRealism"
-#base = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
+#base = "emilianJR/epiCRealism"
+base = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
 #adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-3")
-#vae = AutoencoderKL.from_single_file("https://huggingface.co/stabilityai/sd-vae-ft-mse-original/vae-ft-mse-840000-ema-pruned.safetensors")
+vae = AutoencoderKL.from_single_file("https://huggingface.co/stabilityai/sd-vae-ft-mse-original/vae-ft-mse-840000-ema-pruned.safetensors")
 #unet = UNet2DConditionModel.from_config("emilianJR/epiCRealism",subfolder="unet").to(device, dtype).load_state_dict(load_file(hf_hub_download("emilianJR/epiCRealism", "unet/diffusion_pytorch_model.safetensors"), device=device), strict=False)
 
 css="""
@@ -128,7 +128,7 @@ def generate_random_string(length):
     return ''.join(random.choice(characters) for _ in range(length))
 
 @spaces.GPU(duration=65)
-def Piper(name,positive_prompt,negative,motion):
+def Piper(positive,negative,motion):
     global last_motion
 
     pipe.unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device), strict=False)
@@ -141,12 +141,12 @@ def Piper(name,positive_prompt,negative,motion):
         last_motion = motion
     
     return pipe(
-        positive_prompt,
+        positive,
         negative_prompt=negative,
         height=1024,
         width=576,
         num_inference_steps=step,
-        guidance_scale=7,
+        guidance_scale=1,
         num_frames=(fps*time)
     )
 
@@ -162,7 +162,7 @@ def infer(pm):
             _do.append(f'{p1}')
         posi = " ".join(_do)
 
-        out = Piper(name,posi,neg,pm["m"])
+        out = Piper(posi,neg,pm["m"])
         export_to_gif(out.frames[0],name,fps=fps)
         return name
 
@@ -184,7 +184,7 @@ def run(m,p1,p2,*result):
 
         return out
 
-pipe = AnimateDiffPipeline.from_pretrained(base, torch_dtype=dtype).to(device)
+pipe = AnimateDiffPipeline.from_pretrained(base, vae=vae, torch_dtype=dtype).to(device)
 pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", beta_schedule="linear")
 pipe.enable_free_init(method="butterworth", use_fast_sampling=False)