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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)): | |
| total_process_steps = 11 | |
| irrelevant_steps = 4 | |
| relevant_steps = total_process_steps - irrelevant_steps # 7 steps | |
| # Create the overall progress bar for the process steps. | |
| overall_bar = tqdm(total=relevant_steps, desc="Overall Process", position=1, dynamic_ncols=True, leave=True) | |
| processed_steps = 0 | |
| # Regex for detecting video generation progress lines. | |
| progress_pattern = re.compile(r"(\d+)%\|.*\| (\d+)/(\d+)") | |
| gen_progress_bar = None | |
| # We'll maintain a persistent sub-progress bar for the current step. | |
| current_sub_bar = None | |
| 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 | |
| ) | |
| for line in iter(process.stdout.readline, ''): | |
| stripped_line = line.strip() | |
| if not stripped_line: | |
| continue | |
| # Check if this is a video generation progress line. | |
| progress_match = progress_pattern.search(stripped_line) | |
| if progress_match: | |
| current = int(progress_match.group(2)) | |
| total = int(progress_match.group(3)) | |
| if gen_progress_bar is None: | |
| gen_progress_bar = tqdm(total=total, desc="Video Generation", position=0, | |
| dynamic_ncols=True, leave=True) | |
| gen_progress_bar.update(current - gen_progress_bar.n) | |
| gen_progress_bar.refresh() | |
| continue | |
| # Check for INFO lines. | |
| if "INFO:" in stripped_line: | |
| # Extract the INFO message. | |
| parts = stripped_line.split("INFO:", 1) | |
| msg = parts[1].strip() if len(parts) > 1 else "" | |
| tqdm.write(stripped_line) # print the log line | |
| # Skip the first few irrelevant INFO lines. | |
| if processed_steps < irrelevant_steps: | |
| processed_steps += 1 | |
| else: | |
| # If there's a current sub-progress bar, mark it complete and close it. | |
| if current_sub_bar is not None: | |
| current_sub_bar.update(1) | |
| current_sub_bar.close() | |
| overall_bar.update(1) | |
| overall_bar.refresh() | |
| # Now create a new sub-progress bar for this new step. | |
| # (It will remain visible until the next INFO message arrives.) | |
| current_sub_bar = tqdm(total=1, desc=msg, position=2, | |
| ncols=120, dynamic_ncols=False, leave=True) | |
| else: | |
| tqdm.write(stripped_line) | |
| # When process ends, if there's an open sub-bar, finish it. | |
| if current_sub_bar is not None: | |
| current_sub_bar.update(1) | |
| current_sub_bar.close() | |
| overall_bar.update(1) | |
| overall_bar.refresh() | |
| process.wait() | |
| if gen_progress_bar: | |
| gen_progress_bar.close() | |
| overall_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) |