import numpy as np
import torch
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import export_to_video
from datetime import datetime

pipe = DiffusionPipeline.from_pretrained(r"J:\Projects\Video-Projects\text-to-video-ms-1.7b", torch_dtype=torch.float16, variant="fp16")
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.enable_model_cpu_offload()
timestamp_str = datetime.now().strftime("%Y-%m-%d-%H%M%S")

output_video_path=f"J:/Projects/Video-Projects/text-to-video-ms-1.7b/output_videos/{timestamp_str}.mp4"
prompt = "Spiderman is surfing"

video_frames = pipe(prompt, num_inference_steps=25).frames
video_frames_np = [np.array(frame) for frame in video_frames]
video_frames_np = np.concatenate(video_frames_np, axis=0)

video_path = export_to_video(video_frames_np,output_video_path)