import gradio as gr import subprocess import os import sys from .common_gui import get_folder_path, add_pre_postfix, scriptdir, list_dirs, setup_environment from .custom_logging import setup_logging # Set up logging log = setup_logging() PYTHON = sys.executable def caption_images( train_data_dir, caption_ext, batch_size, max_data_loader_n_workers, max_length, model_id, prefix, postfix, ): # Check for images_dir_input if train_data_dir == "": log.info("Image folder is missing...") return if caption_ext == "": log.info("Please provide an extension for the caption files.") return log.info(f"GIT captioning files in {train_data_dir}...") run_cmd = [fr"{PYTHON}", fr"{scriptdir}/sd-scripts/finetune/make_captions_by_git.py"] # Add --model_id if provided if model_id != "": run_cmd.append("--model_id") run_cmd.append(fr'{model_id}') # Add other arguments with their values run_cmd.append("--batch_size") run_cmd.append(str(batch_size)) run_cmd.append("--max_data_loader_n_workers") run_cmd.append(str(max_data_loader_n_workers)) run_cmd.append("--max_length") run_cmd.append(str(max_length)) # Add --caption_extension if provided if caption_ext != "": run_cmd.append("--caption_extension") run_cmd.append(caption_ext) # Add the directory containing the training data run_cmd.append(fr"{train_data_dir}") env = setup_environment() # Reconstruct the safe command string for display command_to_run = " ".join(run_cmd) log.info(f"Executing command: {command_to_run}") # Run the command in the sd-scripts folder context subprocess.run(run_cmd, env=env) # Add prefix and postfix add_pre_postfix( folder=train_data_dir, caption_file_ext=caption_ext, prefix=prefix, postfix=postfix, ) log.info("...captioning done") ### # Gradio UI ### def gradio_git_caption_gui_tab( headless=False, default_train_dir=None, ): from .common_gui import create_refresh_button default_train_dir = ( default_train_dir if default_train_dir is not None else os.path.join(scriptdir, "data") ) current_train_dir = default_train_dir def list_train_dirs(path): nonlocal current_train_dir current_train_dir = path return list(list_dirs(path)) with gr.Tab("GIT Captioning"): gr.Markdown( "This utility will use GIT to caption files for each images in a folder." ) with gr.Group(), gr.Row(): train_data_dir = gr.Dropdown( label="Image folder to caption (containing the images to caption)", choices=[""] + list_train_dirs(default_train_dir), value="", interactive=True, allow_custom_value=True, ) create_refresh_button( train_data_dir, lambda: None, lambda: {"choices": list_train_dirs(current_train_dir)}, "open_folder_small", ) button_train_data_dir_input = gr.Button( "📂", elem_id="open_folder_small", elem_classes=["tool"], visible=(not headless), ) button_train_data_dir_input.click( get_folder_path, outputs=train_data_dir, show_progress=False, ) with gr.Row(): caption_ext = gr.Dropdown( label="Caption file extension", choices=[".cap", ".caption", ".txt"], value=".txt", interactive=True, allow_custom_value=True, ) prefix = gr.Textbox( label="Prefix to add to GIT caption", placeholder="(Optional)", interactive=True, ) postfix = gr.Textbox( label="Postfix to add to GIT caption", placeholder="(Optional)", interactive=True, ) batch_size = gr.Number(value=1, label="Batch size", interactive=True) with gr.Row(): max_data_loader_n_workers = gr.Number( value=2, label="Number of workers", interactive=True ) max_length = gr.Number(value=75, label="Max length", interactive=True) model_id = gr.Textbox( label="Model", placeholder="(Optional) model id for GIT in Hugging Face", interactive=True, ) caption_button = gr.Button("Caption images") caption_button.click( caption_images, inputs=[ train_data_dir, caption_ext, batch_size, max_data_loader_n_workers, max_length, model_id, prefix, postfix, ], show_progress=False, ) train_data_dir.change( fn=lambda path: gr.Dropdown(choices=[""] + list_train_dirs(path)), inputs=train_data_dir, outputs=train_data_dir, show_progress=False, )