mirror of
https://github.com/Wan-Video/Wan2.1.git
synced 2025-12-16 12:13:27 +00:00
Merge branch 'dev3' of https://github.com/deepbeepmeep/Wan2GP into dev3
This commit is contained in:
DeepBeepMeep
commit
7d2bb5308c
473
wgp.py
473
wgp.py
@ -31,6 +31,7 @@ from PIL import Image
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import zipfile
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import tempfile
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import atexit
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import shutil
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global_queue_ref = []
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AUTOSAVE_FILENAME = "queue.zip"
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PROMPT_VARS_MAX = 10
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@ -367,120 +368,127 @@ def save_queue_action(state):
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gen = get_gen_info(state)
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queue = gen.get("queue", [])
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if not queue or len(queue) <=1 : # Check if queue is empty or only has the placeholder
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if not queue or len(queue) <=1 :
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gr.Info("Queue is empty. Nothing to save.")
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return None # Return None if nothing to save
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return ""
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# Use an in-memory buffer for the zip file
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zip_buffer = io.BytesIO()
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# Still use a temporary directory *only* for storing images before zipping
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with tempfile.TemporaryDirectory() as tmpdir:
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queue_manifest = []
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image_paths_in_zip = {} # Tracks image PIL object ID -> filename in zip
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file_paths_in_zip = {}
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for task_index, task in enumerate(queue):
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# Skip the placeholder item if it exists
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if task is None or not isinstance(task, dict) or task_index == 0: continue
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if task is None or not isinstance(task, dict) or task.get('id') is None: continue
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params_copy = task.get('params', {}).copy()
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task_id_s = task.get('id', f"task_{task_index}") # Use a different var name
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task_id_s = task.get('id', f"task_{task_index}")
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image_keys = ["image_start", "image_end", "image_refs"]
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video_keys = ["video_guide", "video_mask"]
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for key in image_keys:
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images_pil = params_copy.get(key)
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if images_pil is None:
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continue
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# Ensure images_pil is always a list for processing
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is_originally_list = isinstance(images_pil, list)
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if not is_originally_list:
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images_pil = [images_pil]
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image_filenames_for_json = []
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for img_index, pil_image in enumerate(images_pil):
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# Ensure it's actually a PIL Image object before proceeding
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if not isinstance(pil_image, Image.Image):
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print(f"Warning: Expected PIL Image for key '{key}' in task {task_id_s}, got {type(pil_image)}. Skipping image.")
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continue
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# Use object ID to check if this specific image instance is already saved
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img_id = id(pil_image)
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if img_id in image_paths_in_zip:
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# If already saved, just add its filename to the list
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image_filenames_for_json.append(image_paths_in_zip[img_id])
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continue # Move to the next image in the list
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if img_id in file_paths_in_zip:
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image_filenames_for_json.append(file_paths_in_zip[img_id])
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continue
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# Image not saved yet, create filename and save path
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img_filename_in_zip = f"task{task_id_s}_{key}_{img_index}.png"
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img_save_path = os.path.join(tmpdir, img_filename_in_zip)
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try:
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# Save the image to the temporary directory
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pil_image.save(img_save_path, "PNG")
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image_filenames_for_json.append(img_filename_in_zip)
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# Store the mapping from image ID to its filename in the zip
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image_paths_in_zip[img_id] = img_filename_in_zip
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file_paths_in_zip[img_id] = img_filename_in_zip
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print(f"Saved image: {img_filename_in_zip}")
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except Exception as e:
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print(f"Error saving image {img_filename_in_zip} for task {task_id_s}: {e}")
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# Optionally decide if you want to continue or fail here
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# Update the params_copy with the list of filenames (or single filename)
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if image_filenames_for_json:
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params_copy[key] = image_filenames_for_json if is_originally_list else image_filenames_for_json[0]
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else:
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# If no images were successfully processed for this key, remove it
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params_copy.pop(key, None)
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for key in video_keys:
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video_path_orig = params_copy.get(key)
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if video_path_orig is None or not isinstance(video_path_orig, str):
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continue
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if video_path_orig in file_paths_in_zip:
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params_copy[key] = file_paths_in_zip[video_path_orig]
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continue
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if not os.path.isfile(video_path_orig):
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print(f"Warning: Video file not found for key '{key}' in task {task_id_s}: {video_path_orig}. Skipping video.")
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params_copy.pop(key, None)
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continue
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_, extension = os.path.splitext(video_path_orig)
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vid_filename_in_zip = f"task{task_id_s}_{key}{extension if extension else '.mp4'}"
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vid_save_path = os.path.join(tmpdir, vid_filename_in_zip)
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try:
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shutil.copy2(video_path_orig, vid_save_path)
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params_copy[key] = vid_filename_in_zip
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file_paths_in_zip[video_path_orig] = vid_filename_in_zip
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print(f"Copied video: {video_path_orig} -> {vid_filename_in_zip}")
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except Exception as e:
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print(f"Error copying video {video_path_orig} to {vid_filename_in_zip} for task {task_id_s}: {e}")
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params_copy.pop(key, None)
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# Clean up parameters before adding to manifest
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params_copy.pop('state', None)
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params_copy.pop('start_image_data_base64', None) # Don't need base64 in saved queue
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params_copy.pop('start_image_data_base64', None)
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params_copy.pop('end_image_data_base64', None)
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# Also remove the actual PIL data if it somehow remained
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params_copy.pop('start_image_data', None)
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params_copy.pop('end_image_data', None)
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task.pop('start_image_data', None)
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task.pop('end_image_data', None)
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manifest_entry = {
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"id": task.get('id'),
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"params": params_copy,
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# Keep other necessary top-level task info if needed, like repeats etc.
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# Example: "repeats": task.get('repeats', 1)
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}
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manifest_entry = {k: v for k, v in manifest_entry.items() if v is not None}
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queue_manifest.append(manifest_entry)
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# --- Create queue.json content ---
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manifest_path = os.path.join(tmpdir, "queue.json")
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try:
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with open(manifest_path, 'w', encoding='utf-8') as f:
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# Dump only the relevant manifest data
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json.dump(queue_manifest, f, indent=4)
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except Exception as e:
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print(f"Error writing queue.json: {e}")
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gr.Warning("Failed to create queue manifest.")
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return None # Return None on failure
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return None
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# --- Create the zip file in memory ---
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try:
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with zipfile.ZipFile(zip_buffer, 'w', zipfile.ZIP_DEFLATED) as zf:
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# Add queue.json
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zf.write(manifest_path, arcname="queue.json")
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# Add all unique images that were saved to the temp dir
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for saved_img_rel_path in image_paths_in_zip.values():
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saved_img_abs_path = os.path.join(tmpdir, saved_img_rel_path)
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if os.path.exists(saved_img_abs_path):
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zf.write(saved_img_abs_path, arcname=saved_img_rel_path)
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for file_id, saved_file_rel_path in file_paths_in_zip.items():
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saved_file_abs_path = os.path.join(tmpdir, saved_file_rel_path)
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if os.path.exists(saved_file_abs_path):
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zf.write(saved_file_abs_path, arcname=saved_file_rel_path)
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print(f"Adding to zip: {saved_file_rel_path}")
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else:
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# This shouldn't happen if saving was successful, but good to check
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print(f"Warning: Image file {saved_img_rel_path} not found during zipping.")
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print(f"Warning: File {saved_file_rel_path} (ID: {file_id}) not found during zipping.")
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# --- Prepare for return ---
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# Move buffer position to the beginning
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zip_buffer.seek(0)
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# Read the binary content
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zip_binary_content = zip_buffer.getvalue()
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# Encode as base64 string
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zip_base64 = base64.b64encode(zip_binary_content).decode('utf-8')
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print(f"Queue successfully prepared as base64 string ({len(zip_base64)} chars).")
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return zip_base64
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@ -488,18 +496,19 @@ def save_queue_action(state):
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except Exception as e:
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print(f"Error creating zip file in memory: {e}")
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gr.Warning("Failed to create zip data for download.")
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return None # Return None on failure
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return None
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finally:
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zip_buffer.close()
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def load_queue_action(filepath, state):
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global task_id
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gen = get_gen_info(state)
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original_queue = gen.get("queue", []) # Store original queue for error case
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original_queue = gen.get("queue", [])
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save_path_base = server_config.get("save_path", "outputs")
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loaded_cache_dir = os.path.join(save_path_base, "_loaded_queue_cache")
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if not filepath or not hasattr(filepath, 'name') or not Path(filepath.name).is_file():
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print("[load_queue_action] Warning: No valid file selected or file not found.")
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# Return the current state of the DataFrame
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return update_queue_data(original_queue)
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newly_loaded_queue = []
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@ -509,6 +518,9 @@ def load_queue_action(filepath, state):
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try:
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print(f"[load_queue_action] Attempting to load queue from: {filepath.name}")
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os.makedirs(loaded_cache_dir, exist_ok=True)
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print(f"[load_queue_action] Using cache directory: {loaded_cache_dir}")
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with tempfile.TemporaryDirectory() as tmpdir:
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with zipfile.ZipFile(filepath.name, 'r') as zf:
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if "queue.json" not in zf.namelist(): raise ValueError("queue.json not found in zip file")
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@ -523,7 +535,6 @@ def load_queue_action(filepath, state):
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print(f"[load_queue_action] Manifest loaded. Processing {len(loaded_manifest)} tasks.")
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for task_index, task_data in enumerate(loaded_manifest):
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# (Keep the existing task processing logic here...)
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if task_data is None or not isinstance(task_data, dict):
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print(f"[load_queue_action] Skipping invalid task data at index {task_index}")
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continue
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@ -531,144 +542,186 @@ def load_queue_action(filepath, state):
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params = task_data.get('params', {})
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task_id_loaded = task_data.get('id', 0)
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max_id_in_file = max(max_id_in_file, task_id_loaded)
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loaded_pil_images = {}
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params['state'] = state
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image_keys = ["image_start", "image_end", "image_refs"]
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params['state'] = state # Add state back temporarily for consistency if needed by internal logic, but it's removed before saving
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video_keys = ["video_guide", "video_mask"]
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loaded_pil_images = {}
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loaded_video_paths = {}
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for key in image_keys:
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image_filenames = params.get(key)
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if image_filenames is None: continue
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is_list = isinstance(image_filenames, list)
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if not is_list: image_filenames = [image_filenames]
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loaded_pils = []
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for img_filename_in_zip in image_filenames:
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if not isinstance(img_filename_in_zip, str): continue
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if not isinstance(img_filename_in_zip, str):
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print(f"[load_queue_action] Warning: Non-string filename found for image key '{key}'. Skipping.")
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continue
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img_load_path = os.path.join(tmpdir, img_filename_in_zip)
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if not os.path.exists(img_load_path):
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print(f"[load_queue_action] Image file not found during load: {img_load_path}")
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print(f"[load_queue_action] Image file not found in extracted data: {img_load_path}. Skipping.")
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continue
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try:
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pil_image = Image.open(img_load_path)
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# Ensure the image data is loaded into memory before the temp dir is cleaned up
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pil_image.load()
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# Convert image right after loading
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converted_image = convert_image(pil_image)
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loaded_pils.append(converted_image)
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pil_image.close() # Close the file handle
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pil_image.close()
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print(f"Loaded image: {img_filename_in_zip} for key {key}")
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except Exception as img_e:
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print(f"[load_queue_action] Error loading image {img_filename_in_zip}: {img_e}")
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if loaded_pils:
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params[key] = loaded_pils if is_list else loaded_pils[0]
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loaded_pil_images[key] = params[key] # Store loaded PILs for preview generation
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else: params.pop(key, None)
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loaded_pil_images[key] = params[key]
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else:
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params.pop(key, None)
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# Generate preview base64 strings
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primary_preview_pil, secondary_preview_pil = None, None
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start_prev_pil_list = loaded_pil_images.get("image_start")
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end_prev_pil_list = loaded_pil_images.get("image_end")
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ref_prev_pil_list = loaded_pil_images.get("image_refs")
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for key in video_keys:
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video_filename_in_zip = params.get(key)
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if video_filename_in_zip is None or not isinstance(video_filename_in_zip, str):
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continue
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# Extract first image for preview if available
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if start_prev_pil_list:
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primary_preview_pil = start_prev_pil_list[0] if isinstance(start_prev_pil_list, list) and start_prev_pil_list else start_prev_pil_list if not isinstance(start_prev_pil_list, list) else None
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if end_prev_pil_list:
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secondary_preview_pil = end_prev_pil_list[0] if isinstance(end_prev_pil_list, list) and end_prev_pil_list else end_prev_pil_list if not isinstance(end_prev_pil_list, list) else None
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elif ref_prev_pil_list and isinstance(ref_prev_pil_list, list) and ref_prev_pil_list:
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primary_preview_pil = ref_prev_pil_list[0]
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video_load_path = os.path.join(tmpdir, video_filename_in_zip)
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if not os.path.exists(video_load_path):
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print(f"[load_queue_action] Video file not found in extracted data: {video_load_path}. Skipping.")
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params.pop(key, None)
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continue
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persistent_video_path = os.path.join(loaded_cache_dir, video_filename_in_zip)
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try:
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shutil.copy2(video_load_path, persistent_video_path)
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params[key] = persistent_video_path
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loaded_video_paths[key] = persistent_video_path
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print(f"Loaded video: {video_filename_in_zip} -> {persistent_video_path}")
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except Exception as vid_e:
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print(f"[load_queue_action] Error copying video {video_filename_in_zip} to cache: {vid_e}")
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params.pop(key, None)
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primary_preview_pil_list = loaded_pil_images.get("image_start") or loaded_pil_images.get("image_refs")
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secondary_preview_pil_list = loaded_pil_images.get("image_end")
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primary_preview_pil = None
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if primary_preview_pil_list:
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primary_preview_pil = primary_preview_pil_list[0] if isinstance(primary_preview_pil_list, list) else primary_preview_pil_list
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secondary_preview_pil = None
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if secondary_preview_pil_list:
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secondary_preview_pil = secondary_preview_pil_list[0] if isinstance(secondary_preview_pil_list, list) else secondary_preview_pil_list
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# Generate base64 only if PIL image exists
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start_b64 = [pil_to_base64_uri(primary_preview_pil, format="jpeg", quality=70)] if primary_preview_pil else None
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end_b64 = [pil_to_base64_uri(secondary_preview_pil, format="jpeg", quality=70)] if secondary_preview_pil else None
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# Get top-level image data (PIL objects) for runtime task
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top_level_start_image = loaded_pil_images.get("image_start")
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top_level_end_image = loaded_pil_images.get("image_end")
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top_level_start_image = params.get("image_start") or params.get("image_refs")
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top_level_end_image = params.get("image_end")
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# Construct the runtime task dictionary
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runtime_task = {
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"id": task_id_loaded,
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"params": params.copy(), # Use a copy of params
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# Extract necessary params for top level if they exist
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"params": params.copy(),
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"repeats": params.get('repeat_generation', 1),
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"length": params.get('video_length'),
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"steps": params.get('num_inference_steps'),
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"prompt": params.get('prompt'),
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# Store the actual loaded PIL image data here
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"start_image_data": top_level_start_image,
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"end_image_data": top_level_end_image,
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# Store base64 previews generated above
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"start_image_data_base64": start_b64,
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"end_image_data_base64": end_b64,
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}
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newly_loaded_queue.append(runtime_task)
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print(f"[load_queue_action] Processed task {task_index+1}/{len(loaded_manifest)}, ID: {task_id_loaded}")
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print(f"[load_queue_action] Reconstructed task {task_index+1}/{len(loaded_manifest)}, ID: {task_id_loaded}")
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# --- State Update ---
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with lock:
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print("[load_queue_action] Acquiring lock to update state...")
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gen["queue"] = newly_loaded_queue[:] # Replace the queue in the state
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local_queue_copy_for_global_ref = gen["queue"][:] # Copy for global ref update
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current_max_id_in_new_queue = max([t['id'] for t in newly_loaded_queue if 'id' in t] + [0]) # Safer max ID calculation
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gen["queue"] = newly_loaded_queue[:]
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local_queue_copy_for_global_ref = gen["queue"][:]
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# Update global task ID only if the loaded max ID is higher
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if current_max_id_in_new_queue > task_id:
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print(f"[load_queue_action] Updating global task_id from {task_id} to {current_max_id_in_new_queue + 1}")
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task_id = current_max_id_in_new_queue + 1 # Ensure next ID is unique
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current_max_id_in_new_queue = max([t['id'] for t in newly_loaded_queue if 'id' in t] + [0])
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if current_max_id_in_new_queue >= task_id:
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new_task_id = current_max_id_in_new_queue + 1
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print(f"[load_queue_action] Updating global task_id from {task_id} to {new_task_id}")
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task_id = new_task_id
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else:
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print(f"[load_queue_action] Global task_id ({task_id}) is >= max in file ({current_max_id_in_new_queue}). Not changing task_id.")
|
||||
print(f"[load_queue_action] Global task_id ({task_id}) is > max in file ({current_max_id_in_new_queue}). Not changing task_id.")
|
||||
|
||||
gen["prompts_max"] = len(newly_loaded_queue)
|
||||
print("[load_queue_action] State update complete. Releasing lock.")
|
||||
|
||||
# --- Global Reference Update ---
|
||||
if local_queue_copy_for_global_ref is not None:
|
||||
print("[load_queue_action] Updating global queue reference...")
|
||||
update_global_queue_ref(local_queue_copy_for_global_ref)
|
||||
else:
|
||||
# This case should ideally not be reached if state update happens
|
||||
print("[load_queue_action] Warning: Skipping global ref update as local copy is None.")
|
||||
|
||||
print(f"[load_queue_action] Queue load successful. Returning DataFrame update for {len(newly_loaded_queue)} tasks.")
|
||||
# *** Return the DataFrame update object ***
|
||||
return update_queue_data(newly_loaded_queue)
|
||||
|
||||
except (ValueError, zipfile.BadZipFile, FileNotFoundError, Exception) as e:
|
||||
error_message = f"Error during queue load: {e}"
|
||||
print(f"[load_queue_action] Caught error: {error_message}")
|
||||
traceback.print_exc()
|
||||
# Optionally show a Gradio warning/error to the user
|
||||
gr.Warning(f"Failed to load queue: {error_message[:200]}") # Show truncated error
|
||||
gr.Warning(f"Failed to load queue: {error_message[:200]}")
|
||||
|
||||
# *** Return the DataFrame update for the original queue ***
|
||||
print("[load_queue_action] Load failed. Returning DataFrame update for original queue.")
|
||||
return update_queue_data(original_queue)
|
||||
finally:
|
||||
# Clean up the uploaded file object if it exists and has a path
|
||||
if filepath and hasattr(filepath, 'name') and filepath.name and os.path.exists(filepath.name):
|
||||
try:
|
||||
# Gradio often uses temp files, attempting removal is good practice
|
||||
# os.remove(filepath.name)
|
||||
# print(f"[load_queue_action] Cleaned up temporary upload file: {filepath.name}")
|
||||
pass # Let Gradio manage its temp files unless specifically needed
|
||||
except OSError as e:
|
||||
# Ignore errors like "file not found" if already cleaned up
|
||||
print(f"[load_queue_action] Info: Could not remove temp file {filepath.name}: {e}")
|
||||
pass
|
||||
if tempfile.gettempdir() in os.path.abspath(filepath.name):
|
||||
try:
|
||||
os.remove(filepath.name)
|
||||
print(f"[load_queue_action] Removed temporary upload file: {filepath.name}")
|
||||
except OSError as e:
|
||||
print(f"[load_queue_action] Info: Could not remove temp file {filepath.name}: {e}")
|
||||
else:
|
||||
print(f"[load_queue_action] Info: Did not remove non-temporary file: {filepath.name}")
|
||||
|
||||
def clear_queue_action(state):
|
||||
gen = get_gen_info(state)
|
||||
queue = gen.get("queue", [])
|
||||
if not queue:
|
||||
gr.Info("Queue is already empty.")
|
||||
return update_queue_data([])
|
||||
aborted_current = False
|
||||
cleared_pending = False
|
||||
|
||||
with lock:
|
||||
queue.clear()
|
||||
gen["prompts_max"] = 0
|
||||
if "in_progress" in gen and gen["in_progress"]:
|
||||
print("Clear Queue: Signalling abort for in-progress task.")
|
||||
gen["abort"] = True
|
||||
gen["extra_orders"] = 0
|
||||
if wan_model is not None:
|
||||
wan_model._interrupt = True
|
||||
aborted_current = True
|
||||
|
||||
if queue:
|
||||
if len(queue) > 1 or (len(queue) == 1 and queue[0] is not None and queue[0].get('id') is not None):
|
||||
print(f"Clear Queue: Clearing {len(queue)} tasks from queue.")
|
||||
queue.clear()
|
||||
cleared_pending = True
|
||||
else:
|
||||
pass
|
||||
|
||||
if aborted_current or cleared_pending:
|
||||
gen["prompts_max"] = 0
|
||||
|
||||
if aborted_current and cleared_pending:
|
||||
gr.Info("Queue cleared and current generation aborted.")
|
||||
elif aborted_current:
|
||||
gr.Info("Current generation aborted.")
|
||||
elif cleared_pending:
|
||||
gr.Info("Queue cleared.")
|
||||
else:
|
||||
gr.Info("Queue is already empty or only contains the active task (which wasn't aborted now).")
|
||||
|
||||
gr.Info("Queue cleared.")
|
||||
return update_queue_data([])
|
||||
|
||||
def quit_application():
|
||||
print("Save and Quit requested...")
|
||||
autosave_queue()
|
||||
import signal
|
||||
os.kill(os.getpid(), signal.SIGINT)
|
||||
|
||||
def autosave_queue():
|
||||
global global_queue_ref
|
||||
if not global_queue_ref:
|
||||
@ -682,14 +735,20 @@ def autosave_queue():
|
||||
|
||||
def _save_queue_to_file(queue_to_save, output_filename):
|
||||
if not queue_to_save: return None
|
||||
|
||||
with tempfile.TemporaryDirectory() as tmpdir:
|
||||
queue_manifest = []
|
||||
image_paths_in_zip = {}
|
||||
file_paths_in_zip = {}
|
||||
|
||||
for task_index, task in enumerate(queue_to_save):
|
||||
if task is None or not isinstance(task, dict): continue
|
||||
if task is None or not isinstance(task, dict) or task.get('id') is None: continue
|
||||
|
||||
params_copy = task.get('params', {}).copy()
|
||||
task_id_s = task.get('id', f"task_{task_index}")
|
||||
|
||||
image_keys = ["image_start", "image_end", "image_refs"]
|
||||
video_keys = ["video_guide", "video_mask"]
|
||||
|
||||
for key in image_keys:
|
||||
images_pil = params_copy.get(key)
|
||||
if images_pil is None: continue
|
||||
@ -699,38 +758,72 @@ def autosave_queue():
|
||||
for img_index, pil_image in enumerate(images_pil):
|
||||
if not isinstance(pil_image, Image.Image): continue
|
||||
img_id = id(pil_image)
|
||||
if img_id in image_paths_in_zip:
|
||||
image_filenames_for_json.append(image_paths_in_zip[img_id])
|
||||
if img_id in file_paths_in_zip:
|
||||
image_filenames_for_json.append(file_paths_in_zip[img_id])
|
||||
continue
|
||||
img_filename_in_zip = f"task{task_id_s}_{key}_{img_index}.png"
|
||||
img_save_path = os.path.join(tmpdir, img_filename_in_zip)
|
||||
try:
|
||||
pil_image.save(img_save_path, "PNG")
|
||||
image_filenames_for_json.append(img_filename_in_zip)
|
||||
image_paths_in_zip[img_id] = img_filename_in_zip
|
||||
file_paths_in_zip[img_id] = img_filename_in_zip
|
||||
except Exception as e:
|
||||
print(f"Autosave error saving image {img_filename_in_zip}: {e}")
|
||||
if image_filenames_for_json:
|
||||
params_copy[key] = image_filenames_for_json if is_list else image_filenames_for_json[0]
|
||||
else:
|
||||
params_copy.pop(key, None)
|
||||
|
||||
for key in video_keys:
|
||||
video_path_orig = params_copy.get(key)
|
||||
if video_path_orig is None or not isinstance(video_path_orig, str):
|
||||
continue
|
||||
|
||||
if video_path_orig in file_paths_in_zip:
|
||||
params_copy[key] = file_paths_in_zip[video_path_orig]
|
||||
continue
|
||||
|
||||
if not os.path.isfile(video_path_orig):
|
||||
print(f"Warning (Autosave): Video file not found for key '{key}' in task {task_id_s}: {video_path_orig}. Skipping.")
|
||||
params_copy.pop(key, None)
|
||||
continue
|
||||
|
||||
_, extension = os.path.splitext(video_path_orig)
|
||||
vid_filename_in_zip = f"task{task_id_s}_{key}{extension if extension else '.mp4'}"
|
||||
vid_save_path = os.path.join(tmpdir, vid_filename_in_zip)
|
||||
|
||||
try:
|
||||
shutil.copy2(video_path_orig, vid_save_path)
|
||||
params_copy[key] = vid_filename_in_zip
|
||||
file_paths_in_zip[video_path_orig] = vid_filename_in_zip
|
||||
except Exception as e:
|
||||
print(f"Error (Autosave) copying video {video_path_orig} to {vid_filename_in_zip} for task {task_id_s}: {e}")
|
||||
params_copy.pop(key, None)
|
||||
params_copy.pop('state', None)
|
||||
params_copy.pop('start_image_data_base64', None)
|
||||
params_copy.pop('end_image_data_base64', None)
|
||||
params_copy.pop('start_image_data', None)
|
||||
params_copy.pop('end_image_data', None)
|
||||
|
||||
manifest_entry = {
|
||||
"id": task.get('id'), "params": params_copy,
|
||||
"id": task.get('id'),
|
||||
"params": params_copy,
|
||||
}
|
||||
manifest_entry = {k: v for k, v in manifest_entry.items() if v is not None}
|
||||
queue_manifest.append(manifest_entry)
|
||||
|
||||
manifest_path = os.path.join(tmpdir, "queue.json")
|
||||
with open(manifest_path, 'w', encoding='utf-8') as f: json.dump(queue_manifest, f, indent=4)
|
||||
with zipfile.ZipFile(output_filename, 'w', zipfile.ZIP_DEFLATED) as zf:
|
||||
zf.write(manifest_path, arcname="queue.json")
|
||||
for saved_img_rel_path in image_paths_in_zip.values():
|
||||
saved_img_abs_path = os.path.join(tmpdir, saved_img_rel_path)
|
||||
if os.path.exists(saved_img_abs_path):
|
||||
zf.write(saved_img_abs_path, arcname=saved_img_rel_path)
|
||||
for saved_file_rel_path in file_paths_in_zip.values():
|
||||
saved_file_abs_path = os.path.join(tmpdir, saved_file_rel_path)
|
||||
if os.path.exists(saved_file_abs_path):
|
||||
zf.write(saved_file_abs_path, arcname=saved_file_rel_path)
|
||||
else:
|
||||
print(f"Warning (Autosave): File {saved_file_rel_path} not found during zipping.")
|
||||
return output_filename
|
||||
return None # Should not happen if queue has items
|
||||
return None
|
||||
|
||||
saved_path = _save_queue_to_file(global_queue_ref, AUTOSAVE_FILENAME)
|
||||
|
||||
@ -745,17 +838,15 @@ def autosave_queue():
|
||||
|
||||
def autoload_queue(state):
|
||||
global task_id
|
||||
# Initial check using the original state
|
||||
try:
|
||||
gen = get_gen_info(state) # Make sure initial state is a dict
|
||||
gen = get_gen_info(state)
|
||||
original_queue = gen.get("queue", [])
|
||||
except AttributeError:
|
||||
print("[autoload_queue] Error: Initial state is not a dictionary. Cannot autoload.")
|
||||
# Return default values indicating no load occurred and the state is unchanged
|
||||
return gr.update(visible=False), False, state # Return an empty DF update
|
||||
return gr.update(visible=False), False, state
|
||||
|
||||
loaded_flag = False
|
||||
dataframe_update = update_queue_data(original_queue) # Default update is the original queue
|
||||
dataframe_update = update_queue_data(original_queue)
|
||||
|
||||
if not original_queue and Path(AUTOSAVE_FILENAME).is_file():
|
||||
print(f"Autoloading queue from {AUTOSAVE_FILENAME}...")
|
||||
@ -763,40 +854,56 @@ def autoload_queue(state):
|
||||
def __init__(self, name):
|
||||
self.name = name
|
||||
mock_filepath = MockFile(AUTOSAVE_FILENAME)
|
||||
|
||||
# Call load_queue_action, it modifies 'state' internally and returns a DataFrame update
|
||||
dataframe_update = load_queue_action(mock_filepath, state)
|
||||
|
||||
# Now check the 'state' dictionary which should have been modified by load_queue_action
|
||||
gen = get_gen_info(state) # Use the (potentially) modified state dictionary
|
||||
gen = get_gen_info(state)
|
||||
loaded_queue_after_action = gen.get("queue", [])
|
||||
|
||||
if loaded_queue_after_action: # Check if the queue in the state is now populated
|
||||
if loaded_queue_after_action:
|
||||
print(f"Autoload successful. Loaded {len(loaded_queue_after_action)} tasks into state.")
|
||||
loaded_flag = True
|
||||
# Global ref update was already done inside load_queue_action if successful
|
||||
else:
|
||||
print("Autoload attempted but queue in state remains empty (file might be empty or invalid).")
|
||||
# Ensure state reflects empty queue if load failed but file existed
|
||||
with lock:
|
||||
gen["queue"] = []
|
||||
gen["prompts_max"] = 0
|
||||
update_global_queue_ref([])
|
||||
dataframe_update = update_queue_data([]) # Ensure UI shows empty queue
|
||||
dataframe_update = update_queue_data([])
|
||||
|
||||
else: # Handle cases where autoload shouldn't happen
|
||||
else:
|
||||
if original_queue:
|
||||
print("Autoload skipped: Queue is not empty.")
|
||||
update_global_queue_ref(original_queue) # Ensure global ref matches current state
|
||||
dataframe_update = update_queue_data(original_queue) # UI should show current queue
|
||||
update_global_queue_ref(original_queue)
|
||||
dataframe_update = update_queue_data(original_queue)
|
||||
else:
|
||||
print(f"Autoload skipped: {AUTOSAVE_FILENAME} not found.")
|
||||
update_global_queue_ref([]) # Ensure global ref is empty
|
||||
dataframe_update = update_queue_data([]) # UI should show empty queue
|
||||
update_global_queue_ref([])
|
||||
dataframe_update = update_queue_data([])
|
||||
|
||||
# Return the DataFrame update needed for the UI, the flag, and the final state dictionary
|
||||
return dataframe_update, loaded_flag, state
|
||||
|
||||
def run_autoload_and_prepare_ui(current_state):
|
||||
df_update, loaded_flag, modified_state = autoload_queue(current_state)
|
||||
should_start_processing = loaded_flag
|
||||
accordion_update = gr.Accordion(open=True) if loaded_flag else gr.update()
|
||||
return df_update, gr.update(visible=loaded_flag), accordion_update, should_start_processing, modified_state
|
||||
|
||||
def start_processing_if_needed(should_start, current_state):
|
||||
if not isinstance(current_state, dict) or 'gen' not in current_state:
|
||||
yield "Error: Invalid state received before processing."
|
||||
return
|
||||
if should_start:
|
||||
yield from process_tasks(current_state)
|
||||
else:
|
||||
yield None
|
||||
|
||||
def finalize_generation_with_state(current_state):
|
||||
if not isinstance(current_state, dict) or 'gen' not in current_state:
|
||||
return gr.update(), gr.update(interactive=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False, value=""), gr.update(), current_state
|
||||
|
||||
gallery_update, abort_btn_update, gen_btn_update, add_queue_btn_update, current_gen_col_update, gen_info_update = finalize_generation(current_state)
|
||||
accordion_update = gr.Accordion(open=False) if len(get_gen_info(current_state).get("queue", [])) <= 1 else gr.update()
|
||||
return gallery_update, abort_btn_update, gen_btn_update, add_queue_btn_update, current_gen_col_update, gen_info_update, accordion_update, current_state
|
||||
|
||||
def get_queue_table(queue):
|
||||
data = []
|
||||
@ -1179,7 +1286,6 @@ text_encoder_choices = ["ckpts/models_t5_umt5-xxl-enc-bf16.safetensors", "ckpts/
|
||||
server_config_filename = "wgp_config.json"
|
||||
|
||||
if not os.path.isfile(server_config_filename) and os.path.isfile("gradio_config.json"):
|
||||
import shutil
|
||||
shutil.move("gradio_config.json", server_config_filename)
|
||||
|
||||
if not Path(server_config_filename).is_file():
|
||||
@ -2984,7 +3090,6 @@ def download_loras():
|
||||
lora_dir = get_lora_dir(get_model_filename("i2v"), quantizeTransformer)
|
||||
log_path = os.path.join(lora_dir, "log.txt")
|
||||
if not os.path.isfile(log_path):
|
||||
import shutil
|
||||
tmp_path = os.path.join(lora_dir, "tmp_lora_dowload")
|
||||
import glob
|
||||
snapshot_download(repo_id="DeepBeepMeep/Wan2.1", allow_patterns="loras_i2v/*", local_dir= tmp_path)
|
||||
@ -3484,7 +3589,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
with gr.Row():
|
||||
onemore_btn = gr.Button("One More Sample Please !")
|
||||
abort_btn = gr.Button("Abort")
|
||||
|
||||
with gr.Accordion("Queue Management", open=False) as queue_accordion:
|
||||
queue_df = gr.DataFrame(
|
||||
headers=["Qty","Prompt", "Length","Steps","", "", "", "", ""],
|
||||
datatype=[ "str","markdown","str", "markdown", "markdown", "markdown", "str", "str", "str"],
|
||||
@ -3494,14 +3599,15 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
wrap=True,
|
||||
value=[],
|
||||
line_breaks= True,
|
||||
visible= False,
|
||||
visible= True,
|
||||
elem_id="queue_df"
|
||||
)
|
||||
with gr.Row():
|
||||
queue_zip_base64_output = gr.Text(visible=False)
|
||||
save_queue_btn = gr.DownloadButton("Save Queue", size="sm")
|
||||
load_queue_btn = gr.UploadButton("Load Queue", file_types=[".zip"], size="sm")
|
||||
clear_queue_btn = gr.Button("Clear Queue", size="sm", variant="stop")
|
||||
with gr.Row():
|
||||
queue_zip_base64_output = gr.Text(visible=False)
|
||||
save_queue_btn = gr.DownloadButton("Save Queue", size="sm")
|
||||
load_queue_btn = gr.UploadButton("Load Queue", file_types=[".zip"], size="sm")
|
||||
clear_queue_btn = gr.Button("Clear Queue", size="sm", variant="stop")
|
||||
quit_button = gr.Button("Save and Quit", size="sm", variant="secondary")
|
||||
trigger_zip_download_js = """
|
||||
(base64String) => {
|
||||
if (!base64String) {
|
||||
@ -3544,14 +3650,37 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
js=trigger_zip_download_js
|
||||
)
|
||||
|
||||
should_start_flag = gr.State(False)
|
||||
load_queue_btn.upload(
|
||||
fn=load_queue_action,
|
||||
inputs=[load_queue_btn, state],
|
||||
outputs=[queue_df]
|
||||
).then(
|
||||
fn=lambda s: gr.update(visible=bool(get_gen_info(s).get("queue",[]))),
|
||||
fn=lambda s: (gr.update(visible=bool(get_gen_info(s).get("queue",[]))), gr.Accordion(open=True)) if bool(get_gen_info(s).get("queue",[])) else (gr.update(visible=False), gr.update()),
|
||||
inputs=[state],
|
||||
outputs=[current_gen_column]
|
||||
outputs=[current_gen_column, queue_accordion]
|
||||
).then(
|
||||
fn=lambda s: (
|
||||
(gr.Button(visible=False), gr.Button(visible=True), gr.Column(visible=True), True)
|
||||
if bool(get_gen_info(s).get("queue",[]))
|
||||
else (gr.Button(visible=True), gr.Button(visible=False), gr.Column(visible=False), False)
|
||||
),
|
||||
inputs=[state],
|
||||
outputs=[generate_btn, add_to_queue_btn, current_gen_column, should_start_flag]
|
||||
).then(
|
||||
fn=start_processing_if_needed,
|
||||
inputs=[should_start_flag, state],
|
||||
outputs=[gen_status],
|
||||
trigger_mode="once"
|
||||
).then(
|
||||
fn=finalize_generation_with_state,
|
||||
inputs=[state],
|
||||
outputs=[output, abort_btn, generate_btn, add_to_queue_btn, current_gen_column, gen_info, queue_accordion, state],
|
||||
trigger_mode="always_last"
|
||||
).then(
|
||||
unload_model_if_needed,
|
||||
inputs= [state],
|
||||
outputs= []
|
||||
)
|
||||
|
||||
clear_queue_btn.click(
|
||||
@ -3559,9 +3688,14 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
inputs=[state],
|
||||
outputs=[queue_df]
|
||||
).then(
|
||||
fn=lambda: gr.update(visible=False),
|
||||
fn=lambda: (gr.update(visible=False), gr.Accordion(open=False)),
|
||||
inputs=None,
|
||||
outputs=[current_gen_column]
|
||||
outputs=[current_gen_column, queue_accordion]
|
||||
)
|
||||
quit_button.click(
|
||||
fn=quit_application,
|
||||
inputs=[],
|
||||
outputs=[]
|
||||
)
|
||||
|
||||
extra_inputs = prompt_vars + [wizard_prompt, wizard_variables_var, wizard_prompt_activated_var, video_prompt_column, image_prompt_column,
|
||||
@ -3644,6 +3778,10 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
).then(finalize_generation,
|
||||
inputs= [state],
|
||||
outputs= [output, abort_btn, generate_btn, add_to_queue_btn, current_gen_column, gen_info]
|
||||
).then(
|
||||
fn=lambda s: gr.Accordion(open=False) if len(get_gen_info(s).get("queue", [])) <= 1 else gr.update(),
|
||||
inputs=[state],
|
||||
outputs=[queue_accordion]
|
||||
).then(unload_model_if_needed,
|
||||
inputs= [state],
|
||||
outputs= []
|
||||
@ -3658,6 +3796,10 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
).then(fn=process_prompt_and_add_tasks,
|
||||
inputs = [state, model_choice],
|
||||
outputs=queue_df
|
||||
).then(
|
||||
fn=lambda s: gr.Accordion(open=True) if len(get_gen_info(s).get("queue", [])) > 1 else gr.update(), # Expand if queue has items (len > 1 assumes placeholder)
|
||||
inputs=[state],
|
||||
outputs=[queue_accordion]
|
||||
).then(
|
||||
fn=update_status,
|
||||
inputs = [state],
|
||||
@ -3675,7 +3817,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
|
||||
gen_info,
|
||||
prompt, wizard_prompt, wizard_prompt_activated_var, wizard_variables_var,
|
||||
prompt_column_advanced, prompt_column_wizard, prompt_column_wizard_vars,
|
||||
advanced_row, image_prompt_column, video_prompt_column,
|
||||
advanced_row, image_prompt_column, video_prompt_column, queue_accordion,
|
||||
*prompt_vars
|
||||
)
|
||||
|
||||
@ -4158,7 +4300,7 @@ def create_demo():
|
||||
gen_info,
|
||||
prompt, wizard_prompt, wizard_prompt_activated_var, wizard_variables_var,
|
||||
prompt_column_advanced, prompt_column_wizard, prompt_column_wizard_vars,
|
||||
advanced_row, image_prompt_column, video_prompt_column,
|
||||
advanced_row, image_prompt_column, video_prompt_column, queue_accordion,
|
||||
*prompt_vars_outputs
|
||||
) = generate_video_tab(model_choice=model_choice, header=header)
|
||||
with gr.Tab("Informations"):
|
||||
@ -4172,30 +4314,11 @@ def create_demo():
|
||||
generate_about_tab()
|
||||
|
||||
should_start_flag = gr.State(False)
|
||||
def run_autoload_and_prepare_ui(current_state):
|
||||
df_update, loaded_flag, modified_state = autoload_queue(current_state)
|
||||
should_start_processing = loaded_flag
|
||||
return df_update, gr.update(visible=loaded_flag), should_start_processing, modified_state
|
||||
|
||||
def start_processing_if_needed(should_start, current_state):
|
||||
if not isinstance(current_state, dict) or 'gen' not in current_state:
|
||||
yield "Error: Invalid state received before processing."
|
||||
return
|
||||
if should_start:
|
||||
yield from process_tasks(current_state)
|
||||
else:
|
||||
yield "Autoload complete. Processing not started."
|
||||
|
||||
def finalize_generation_with_state(current_state):
|
||||
if not isinstance(current_state, dict) or 'gen' not in current_state:
|
||||
return gr.update(), gr.update(interactive=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False, value=""), current_state
|
||||
gallery_update, abort_btn_update, gen_btn_update, add_queue_btn_update, current_gen_col_update, gen_info_update = finalize_generation(current_state)
|
||||
return gallery_update, abort_btn_update, gen_btn_update, add_queue_btn_update, current_gen_col_update, gen_info_update, current_state
|
||||
|
||||
demo.load(
|
||||
fn=run_autoload_and_prepare_ui,
|
||||
inputs=[state],
|
||||
outputs=[queue_df, current_gen_column, should_start_flag, state]
|
||||
outputs=[queue_df, current_gen_column, queue_accordion, should_start_flag, state]
|
||||
).then(
|
||||
fn=start_processing_if_needed,
|
||||
inputs=[should_start_flag, state],
|
||||
@ -4204,7 +4327,7 @@ def create_demo():
|
||||
).then(
|
||||
fn=finalize_generation_with_state,
|
||||
inputs=[state],
|
||||
outputs=[output, abort_btn, generate_btn, add_to_queue_btn, current_gen_column, gen_info, state],
|
||||
outputs=[output, abort_btn, generate_btn, add_to_queue_btn, current_gen_column, gen_info, queue_accordion, state],
|
||||
trigger_mode="always_last"
|
||||
)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user