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import gradio as gr
import re
import subprocess
from tqdm import tqdm
from huggingface_hub import snapshot_download
#Download model
snapshot_download(
repo_id = "Wan-AI/Wan2.1-T2V-1.3B",
local_dir = "./Wan2.1-T2V-1.3B"
)
def infer(prompt, progress=gr.Progress(track_tqdm=True)):
command = [
"python", "-u", "-m", "generate", # using -u for unbuffered output and omitting .py extension
"--task", "t2v-1.3B",
"--size", "832*480",
"--ckpt_dir", "./Wan2.1-T2V-1.3B",
"--sample_shift", "8",
"--sample_guide_scale", "6",
"--prompt", prompt,
"--save_file", "generated_video.mp4"
]
# Start the process with unbuffered output and combine stdout and stderr.
process = subprocess.Popen(
command,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True,
bufsize=1 # line-buffered
)
progress_bar = None
# Regex pattern to capture lines like " 10%|█ | 5/50"
progress_pattern = re.compile(r"(\d+)%\|.*\| (\d+)/(\d+)")
for line in iter(process.stdout.readline, ''):
# Try to parse progress info from the line
match = progress_pattern.search(line)
if match:
current = int(match.group(2))
total = int(match.group(3))
if progress_bar is None:
progress_bar = tqdm(total=total, desc="Video Generation Progress")
# Update the progress bar only if progress has advanced
progress_bar.update(current - progress_bar.n)
else:
# Print any other log lines as they are
print(line, end="")
process.wait()
if progress_bar is not None:
progress_bar.close()
if process.returncode == 0:
print("Command executed successfully.")
return "generated_video.mp4"
else:
print("Error executing command.")
raise Exception("Error executing command")
with gr.Blocks() as demo:
with gr.Column():
gr.Markdown("# Wan 2.1")
prompt = gr.Textbox(label="Prompt")
submit_btn = gr.Button("Submit")
video_res = gr.Video(label="Generated Video")
submit_btn.click(
fn = infer,
inputs = [prompt],
outputs = [video_res]
)
demo.queue().launch(show_error=True, show_api=False, ssr_mode=False) |