Update app.py

app.py

@@ -1,6 +1,6 @@
 import torch
 import gradio as gr
-from diffusers import AnimateDiffSparseControlNetPipeline, AutoencoderKL, MotionAdapter, SparseControlNetModel
+from diffusers import AnimateDiffSparseControlNetPipeline, AutoencoderKL, MotionAdapter, SparseControlNetModel, AnimateDiffPipeline, EulerAncestralDiscreteScheduler
 from diffusers.schedulers import DPMSolverMultistepScheduler
 from diffusers.utils import export_to_gif, load_image
 
@@ -45,7 +45,31 @@ def generate_video(prompt, negative_prompt, num_inference_steps, conditioning_fr
     export_to_gif(video, "output.gif")
     return "output.gif"
 
-demo = gr.Interface(
+def generate_simple_video(prompt):
+    adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2", torch_dtype=torch.float16).to(device)
+    pipe = AnimateDiffPipeline.from_pretrained("SG161222/Realistic_Vision_V6.0_B1_noVAE", motion_adapter=adapter, torch_dtype=torch.float16).to(device)
+    pipe.scheduler = EulerAncestralDiscreteScheduler(
+        beta_schedule="linear",
+        beta_start=0.00085,
+        beta_end=0.012,
+    )
+    
+    pipe.enable_free_noise()
+    pipe.vae.enable_slicing()
+    pipe.enable_model_cpu_offload()
+
+    frames = pipe(
+        prompt,
+        num_frames=64,
+        num_inference_steps=20,
+        guidance_scale=7.0,
+        decode_chunk_size=2,
+    ).frames[0]
+    
+    export_to_gif(frames, "simple_output.gif")
+    return "simple_output.gif"
+
+demo1 = gr.Interface(
     fn=generate_video,
     inputs=[
         gr.Textbox(label="Prompt", default="an aerial view of a cyberpunk city, night time, neon lights, masterpiece, high quality"),
@@ -55,8 +79,19 @@ demo = gr.Interface(
         gr.Slider(label="ControlNet Conditioning Scale", minimum=0.1, maximum=2.0, step=0.1, default=1.0)
     ],
     outputs=gr.Image(label="Generated Video"),
-    title="Generate Video with AnimateDiff",
+    title="Generate Video with AnimateDiffSparseControlNetPipeline",
     description="Generate a video using the AnimateDiffSparseControlNetPipeline."
 )
 
-demo.launch(server_name="0.0.0.0", server_port=7910)
+demo2 = gr.Interface(
+    fn=generate_simple_video,
+    inputs=gr.Textbox(label="Prompt", default="An astronaut riding a horse on Mars."),
+    outputs=gr.Image(label="Generated Simple Video"),
+    title="Generate Simple Video with AnimateDiff",
+    description="Generate a simple video using the AnimateDiffPipeline."
+)
+
+demo = gr.TabbedInterface([demo1, demo2], ["Advanced Video Generation", "Simple Video Generation"])
+
+demo.launch()
+#demo.launch(server_name="0.0.0.0", server_port=7910)