Update app.py

app.py

@@ -3,6 +3,7 @@ import torch
 import gradio as gr
 from diffusers import CogVideoXPipeline
 from diffusers.utils import export_to_video
+from PIL import Image
 
 # ────────────────────────────────────────────────────────────
 # 1. Load & optimize the CogVideoX pipeline with CPU offload
@@ -32,7 +33,7 @@ def parse_resolution(res_str: str):
 # ────────────────────────────────────────────────────────────
 # 3. GPU‑decorated video generation function
 # ────────────────────────────────────────────────────────────
-@spaces.GPU(duration=1200)  # allow up to 10 minutes of GPU time
+@spaces.GPU(duration=180)  # allow up to 180s of GPU time
 def generate_video(
     prompt: str,
     steps: int,
@@ -40,31 +41,35 @@ def generate_video(
     fps: int,
     resolution: str
 ) -> str:
-    # 3.1 Parse & sanitize resolution
-    height, width = parse_resolution(resolution)
+    # 3.1 Determine target resolution and native resolution
+    target_h, target_w = parse_resolution(resolution)
 
-    # 3.2 Run the diffusion pipeline
+    # 3.2 Run the diffusion pipeline at native resolution
     output = pipe(
         prompt=prompt,
         num_inference_steps=steps,
         num_frames=frames,
-        height=height,
-        width=width
     )
-    video_frames = output.frames[0]
+    video_frames = output.frames[0]  # list of PIL Images at native size
 
-    # 3.3 Export to MP4 (H.264) with chosen FPS
-    video_path = export_to_video(video_frames, "generated.mp4", fps=fps)
+    # 3.3 Resize frames to user-specified resolution
+    resized_frames = [
+        frame.resize((target_w, target_h), Image.LANCZOS)
+        for frame in video_frames
+    ]
+
+    # 3.4 Export to MP4 (H.264) with chosen FPS
+    video_path = export_to_video(resized_frames, "generated.mp4", fps=fps)
     return video_path
 
 # ────────────────────────────────────────────────────────────
 # 4. Build the Gradio interface with interactive controls
 # ────────────────────────────────────────────────────────────
-with gr.Blocks(title="Textual Imagination: A text to video systhesis") as demo:
+with gr.Blocks(title="Textual Imagination: A text to video synthesis") as demo:
     gr.Markdown(
         """
-        # 🎞️ Textual Imagination: A text to video systhesis 
-        Generate videos from text prompt.  
+        # 🎞️ Textual Imagination: A text to video synthesis
+        Generate videos from text prompts.
         Adjust inference steps, frame count, fps, and resolution below.
         """
     )