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app (1).py

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+import spaces
+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
+# ────────────────────────────────────────────────────────────
+pipe = CogVideoXPipeline.from_pretrained(
+    "THUDM/CogVideoX1.5-5B",
+    torch_dtype=torch.bfloat16
+)
+pipe.enable_model_cpu_offload()   # auto move submodules between CPU/GPU
+pipe.vae.enable_slicing()         # slice VAE for extra VRAM savings
+
+# ────────────────────────────────────────────────────────────
+# 2. Resolution parsing & sanitization
+# ────────────────────────────────────────────────────────────
+def make_divisible_by_8(x: int) -> int:
+    return (x // 8) * 8
+
+def parse_resolution(res_str: str):
+    """
+    Convert strings like "480p" into (height, width) both divisible by 8
+    while preserving ~16:9 aspect ratio.
+    """
+    h = int(res_str.rstrip("p"))
+    w = int(h * 16 / 9)
+    return make_divisible_by_8(h), make_divisible_by_8(w)
+
+# ────────────────────────────────────────────────────────────
+# 3. GPU‑decorated video generation function
+# ────────────────────────────────────────────────────────────
+@spaces.GPU(duration=180)  # allow up to 180s of GPU time
+def generate_video(
+    prompt: str,
+    steps: int,
+    frames: int,
+    fps: int,
+    resolution: str
+) -> str:
+    # 3.1 Determine target resolution and native resolution
+    target_h, target_w = parse_resolution(resolution)
+
+    # 3.2 Run the diffusion pipeline at native resolution
+    output = pipe(
+        prompt=prompt,
+        num_inference_steps=steps,
+        num_frames=frames,
+    )
+    video_frames = output.frames[0]  # list of PIL Images at native size
+
+    # 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 synthesis") as demo:
+    gr.Markdown(
+        """
+        # 🎞️ Textual Imagination: A text to video synthesis
+        Generate videos from text prompts.
+        Adjust inference steps, frame count, fps, and resolution below.
+        """
+    )
+    with gr.Row():
+        with gr.Column():
+            prompt_input = gr.Textbox(
+                label="Prompt",
+                lines=2
+            )
+            steps_slider = gr.Slider(
+                minimum=1, maximum=100, step=1, value=50,
+                label="Inference Steps"
+            )
+            frames_slider = gr.Slider(
+                minimum=16, maximum=320, step=1, value=161,
+                label="Total Frames"
+            )
+            fps_slider = gr.Slider(
+                minimum=1, maximum=60, step=1, value=16,
+                label="Frames per Second (FPS)"
+            )
+            res_dropdown = gr.Dropdown(
+                choices=["360p", "480p", "720p", "1080p"],
+                value="480p",
+                label="Resolution"
+            )
+            gen_button = gr.Button("Generate Video")
+        with gr.Column():
+            video_output = gr.Video(
+                label="Generated Video",
+                format="mp4"
+            )
+
+    gen_button.click(
+        fn=generate_video,
+        inputs=[prompt_input, steps_slider, frames_slider, fps_slider, res_dropdown],
+        outputs=video_output
+    )
+
+# ────────────────────────────────────────────────────────────
+# 5. Launch: disable SSR so Gradio blocks and stays alive
+# ────────────────────────────────────────────────────────────
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        ssr_mode=False
+    )

requirements (1).txt

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+
+diffusers>=0.30.1
+transformers>=4.44.0
+accelerate>=0.33.0
+torch>=2.0.1
+sentencepiece
+gradio
+imageio>=2.31.6
+imageio-ffmpeg>=0.5.1
+opencv-python>=4.9.0.0
+
+