Spaces:
Running
Running
File size: 1,510 Bytes
feedcc2 33df378 feedcc2 33df378 feedcc2 33df378 feedcc2 33df378 feedcc2 33df378 feedcc2 33df378 feedcc2 315ca65 33df378 315ca65 33df378 feedcc2 33df378 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
import argparse
import subprocess
import os
from huggingface_hub import snapshot_download
# Arguments
parser = argparse.ArgumentParser()
parser.add_argument("--task", type=str, default="t2v-14B")
parser.add_argument("--size", type=str, default="832*480")
parser.add_argument("--frame_num", type=int, default=60)
parser.add_argument("--sample_steps", type=int, default=25)
parser.add_argument("--ckpt_dir", type=str, default="./Wan2.1-T2V-14B")
parser.add_argument("--offload_model", type=str, default="True")
parser.add_argument("--precision", type=str, default="bf16")
parser.add_argument("--prompt", type=str, required=True)
args = parser.parse_args()
# Download model if not available
if not os.path.exists(args.ckpt_dir):
print("🔄 Downloading WAN 2.1 model...")
snapshot_download(repo_id="Wan-AI/Wan2.1-T2V-14B", local_dir=args.ckpt_dir)
# Run Model
command = f"python run_model.py --task {args.task} --size {args.size} --frame_num {args.frame_num} --sample_steps {args.sample_steps} --ckpt_dir {args.ckpt_dir} --offload_model {args.offload_model} --precision {args.precision} --prompt \"{args.prompt}\""
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = process.communicate()
print("🔹 Output:", stdout.decode())
print("🔺 Error:", stderr.decode())
# Check if video was created
if os.path.exists("output.mp4"):
print("✅ Video generated successfully: output.mp4")
else:
print("❌ Error: Video file not found!")
|