531 lines
20 KiB
Python
531 lines
20 KiB
Python
# credit goes to VHS
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import os
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import itertools
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import numpy as np
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import torch
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import cv2
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import folder_paths
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from comfy.utils import common_upscale
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### Utils
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import hashlib
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from typing import Iterable
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import shutil
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import subprocess
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import re
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import uuid
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import server
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from tqdm import tqdm
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BIGMIN = -(2**53-1)
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BIGMAX = (2**53-1)
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DIMMAX = 8192
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def ffmpeg_suitability(path):
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try:
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version = subprocess.run([path, "-version"], check=True,
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capture_output=True).stdout.decode("utf-8")
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except:
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return 0
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score = 0
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#rough layout of the importance of various features
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simple_criterion = [("libvpx", 20),("264",10), ("265",3),
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("svtav1",5),("libopus", 1)]
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for criterion in simple_criterion:
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if version.find(criterion[0]) >= 0:
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score += criterion[1]
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#obtain rough compile year from copyright information
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copyright_index = version.find('2000-2')
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if copyright_index >= 0:
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copyright_year = version[copyright_index+6:copyright_index+9]
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if copyright_year.isnumeric():
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score += int(copyright_year)
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return score
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if "VHS_FORCE_FFMPEG_PATH" in os.environ:
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ffmpeg_path = os.environ.get("VHS_FORCE_FFMPEG_PATH")
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else:
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ffmpeg_paths = []
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try:
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from imageio_ffmpeg import get_ffmpeg_exe
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imageio_ffmpeg_path = get_ffmpeg_exe()
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ffmpeg_paths.append(imageio_ffmpeg_path)
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except:
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if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
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raise
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if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
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ffmpeg_path = imageio_ffmpeg_path
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else:
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system_ffmpeg = shutil.which("ffmpeg")
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if system_ffmpeg is not None:
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ffmpeg_paths.append(system_ffmpeg)
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if os.path.isfile("ffmpeg"):
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ffmpeg_paths.append(os.path.abspath("ffmpeg"))
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if os.path.isfile("ffmpeg.exe"):
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ffmpeg_paths.append(os.path.abspath("ffmpeg.exe"))
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if len(ffmpeg_paths) == 0:
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ffmpeg_path = None
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elif len(ffmpeg_paths) == 1:
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#Evaluation of suitability isn't required, can take sole option
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#to reduce startup time
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ffmpeg_path = ffmpeg_paths[0]
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else:
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ffmpeg_path = max(ffmpeg_paths, key=ffmpeg_suitability)
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gifski_path = os.environ.get("VHS_GIFSKI", None)
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if gifski_path is None:
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gifski_path = os.environ.get("JOV_GIFSKI", None)
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if gifski_path is None:
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gifski_path = shutil.which("gifski")
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def get_sorted_dir_files_from_directory(directory: str, skip_first_images: int=0, select_every_nth: int=1, extensions: Iterable=None):
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directory = directory.strip()
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dir_files = os.listdir(directory)
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dir_files = sorted(dir_files)
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dir_files = [os.path.join(directory, x) for x in dir_files]
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dir_files = list(filter(lambda filepath: os.path.isfile(filepath), dir_files))
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# filter by extension, if needed
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if extensions is not None:
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extensions = list(extensions)
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new_dir_files = []
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for filepath in dir_files:
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ext = "." + filepath.split(".")[-1]
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if ext.lower() in extensions:
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new_dir_files.append(filepath)
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dir_files = new_dir_files
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# start at skip_first_images
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dir_files = dir_files[skip_first_images:]
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dir_files = dir_files[0::select_every_nth]
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return dir_files
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# modified from https://stackoverflow.com/questions/22058048/hashing-a-file-in-python
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def calculate_file_hash(filename: str, hash_every_n: int = 1):
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#Larger video files were taking >.5 seconds to hash even when cached,
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#so instead the modified time from the filesystem is used as a hash
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h = hashlib.sha256()
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h.update(filename.encode())
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h.update(str(os.path.getmtime(filename)).encode())
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return h.hexdigest()
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prompt_queue = server.PromptServer.instance.prompt_queue
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def requeue_workflow_unchecked():
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"""Requeues the current workflow without checking for multiple requeues"""
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currently_running = prompt_queue.currently_running
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(_, _, prompt, extra_data, outputs_to_execute) = next(iter(currently_running.values()))
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#Ensure batch_managers are marked stale
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prompt = prompt.copy()
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for uid in prompt:
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if prompt[uid]['class_type'] == 'VHS_BatchManager':
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prompt[uid]['inputs']['requeue'] = prompt[uid]['inputs'].get('requeue',0)+1
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#execution.py has guards for concurrency, but server doesn't.
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#TODO: Check that this won't be an issue
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number = -server.PromptServer.instance.number
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server.PromptServer.instance.number += 1
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prompt_id = str(server.uuid.uuid4())
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prompt_queue.put((number, prompt_id, prompt, extra_data, outputs_to_execute))
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requeue_guard = [None, 0, 0, {}]
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def requeue_workflow(requeue_required=(-1,True)):
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assert(len(prompt_queue.currently_running) == 1)
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global requeue_guard
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(run_number, _, prompt, _, _) = next(iter(prompt_queue.currently_running.values()))
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if requeue_guard[0] != run_number:
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#Calculate a count of how many outputs are managed by a batch manager
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managed_outputs=0
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for bm_uid in prompt:
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if prompt[bm_uid]['class_type'] == 'VHS_BatchManager':
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for output_uid in prompt:
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if prompt[output_uid]['class_type'] in ["VHS_VideoCombine"]:
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for inp in prompt[output_uid]['inputs'].values():
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if inp == [bm_uid, 0]:
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managed_outputs+=1
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requeue_guard = [run_number, 0, managed_outputs, {}]
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requeue_guard[1] = requeue_guard[1]+1
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requeue_guard[3][requeue_required[0]] = requeue_required[1]
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if requeue_guard[1] == requeue_guard[2] and max(requeue_guard[3].values()):
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requeue_workflow_unchecked()
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def get_audio(file, start_time=0, duration=0):
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args = [ffmpeg_path, "-v", "error", "-i", file]
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if start_time > 0:
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args += ["-ss", str(start_time)]
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if duration > 0:
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args += ["-t", str(duration)]
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try:
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res = subprocess.run(args + ["-f", "wav", "-"],
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stdout=subprocess.PIPE, check=True).stdout
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except subprocess.CalledProcessError as e:
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return False
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return res
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def lazy_eval(func):
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class Cache:
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def __init__(self, func):
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self.res = None
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self.func = func
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def get(self):
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if self.res is None:
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self.res = self.func()
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return self.res
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cache = Cache(func)
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return lambda : cache.get()
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def is_url(url):
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return url.split("://")[0] in ["http", "https"]
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def validate_sequence(path):
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#Check if path is a valid ffmpeg sequence that points to at least one file
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(path, file) = os.path.split(path)
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if not os.path.isdir(path):
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return False
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match = re.search('%0?\d+d', file)
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if not match:
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return False
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seq = match.group()
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if seq == '%d':
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seq = '\\\\d+'
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else:
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seq = '\\\\d{%s}' % seq[1:-1]
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file_matcher = re.compile(re.sub('%0?\d+d', seq, file))
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for file in os.listdir(path):
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if file_matcher.fullmatch(file):
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return True
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return False
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def hash_path(path):
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if path is None:
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return "input"
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if is_url(path):
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return "url"
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return calculate_file_hash(path.strip("\""))
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def validate_path(path, allow_none=False, allow_url=True):
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if path is None:
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return allow_none
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if is_url(path):
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#Probably not feasible to check if url resolves here
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return True if allow_url else "URLs are unsupported for this path"
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if not os.path.isfile(path.strip("\"")):
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return "Invalid file path: {}".format(path)
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return True
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### Utils
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video_extensions = ['webm', 'mp4', 'mkv', 'gif']
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def is_gif(filename) -> bool:
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file_parts = filename.split('.')
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return len(file_parts) > 1 and file_parts[-1] == "gif"
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def target_size(width, height, force_size, custom_width, custom_height) -> tuple[int, int]:
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if force_size == "Custom":
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return (custom_width, custom_height)
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elif force_size == "Custom Height":
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force_size = "?x"+str(custom_height)
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elif force_size == "Custom Width":
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force_size = str(custom_width)+"x?"
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if force_size != "Disabled":
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force_size = force_size.split("x")
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if force_size[0] == "?":
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width = (width*int(force_size[1]))//height
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#Limit to a multple of 8 for latent conversion
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width = int(width)+4 & ~7
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height = int(force_size[1])
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elif force_size[1] == "?":
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height = (height*int(force_size[0]))//width
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height = int(height)+4 & ~7
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width = int(force_size[0])
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else:
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width = int(force_size[0])
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height = int(force_size[1])
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return (width, height)
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def cv_frame_generator(video, force_rate, frame_load_cap, skip_first_frames,
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select_every_nth, meta_batch=None, unique_id=None):
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video_cap = cv2.VideoCapture(video)
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if not video_cap.isOpened():
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raise ValueError(f"{video} could not be loaded with cv.")
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# extract video metadata
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fps = video_cap.get(cv2.CAP_PROP_FPS)
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width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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total_frames = int(video_cap.get(cv2.CAP_PROP_FRAME_COUNT))
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duration = total_frames / fps
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# set video_cap to look at start_index frame
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total_frame_count = 0
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total_frames_evaluated = -1
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frames_added = 0
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base_frame_time = 1 / fps
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prev_frame = None
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if force_rate == 0:
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target_frame_time = base_frame_time
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else:
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target_frame_time = 1/force_rate
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yield (width, height, fps, duration, total_frames, target_frame_time)
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time_offset=target_frame_time - base_frame_time
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while video_cap.isOpened():
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if time_offset < target_frame_time:
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is_returned = video_cap.grab()
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# if didn't return frame, video has ended
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if not is_returned:
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break
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time_offset += base_frame_time
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if time_offset < target_frame_time:
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continue
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time_offset -= target_frame_time
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# if not at start_index, skip doing anything with frame
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total_frame_count += 1
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if total_frame_count <= skip_first_frames:
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continue
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else:
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total_frames_evaluated += 1
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# if should not be selected, skip doing anything with frame
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if total_frames_evaluated%select_every_nth != 0:
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continue
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# opencv loads images in BGR format (yuck), so need to convert to RGB for ComfyUI use
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# follow up: can videos ever have an alpha channel?
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# To my testing: No. opencv has no support for alpha
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unused, frame = video_cap.retrieve()
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# convert frame to comfyui's expected format
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# TODO: frame contains no exif information. Check if opencv2 has already applied
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frame = np.array(frame, dtype=np.float32) / 255.0
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if prev_frame is not None:
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inp = yield prev_frame
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if inp is not None:
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#ensure the finally block is called
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return
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prev_frame = frame
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frames_added += 1
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# if cap exists and we've reached it, stop processing frames
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if frame_load_cap > 0 and frames_added >= frame_load_cap:
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break
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if meta_batch is not None:
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meta_batch.inputs.pop(unique_id)
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meta_batch.has_closed_inputs = True
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if prev_frame is not None:
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yield prev_frame
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def load_video_cv(video: str, force_rate: int, force_size: str,
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custom_width: int,custom_height: int, frame_load_cap: int,
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skip_first_frames: int, select_every_nth: int,
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meta_batch=None, unique_id=None):
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if meta_batch is None or unique_id not in meta_batch.inputs:
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gen = cv_frame_generator(video, force_rate, frame_load_cap, skip_first_frames,
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select_every_nth, meta_batch, unique_id)
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(width, height, fps, duration, total_frames, target_frame_time) = next(gen)
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if meta_batch is not None:
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meta_batch.inputs[unique_id] = (gen, width, height, fps, duration, total_frames, target_frame_time)
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else:
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(gen, width, height, fps, duration, total_frames, target_frame_time) = meta_batch.inputs[unique_id]
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if meta_batch is not None:
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gen = itertools.islice(gen, meta_batch.frames_per_batch)
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#Some minor wizardry to eliminate a copy and reduce max memory by a factor of ~2
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images = torch.from_numpy(np.fromiter(gen, np.dtype((np.float32, (height, width, 3)))))
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if len(images) == 0:
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raise RuntimeError("No frames generated")
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if force_size != "Disabled":
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new_size = target_size(width, height, force_size, custom_width, custom_height)
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if new_size[0] != width or new_size[1] != height:
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s = images.movedim(-1,1)
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s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
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images = s.movedim(1,-1)
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#Setup lambda for lazy audio capture
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audio = lambda : get_audio(video, skip_first_frames * target_frame_time,
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frame_load_cap*target_frame_time*select_every_nth)
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#Adjust target_frame_time for select_every_nth
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target_frame_time *= select_every_nth
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video_info = {
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"source_fps": fps,
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"source_frame_count": total_frames,
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"source_duration": duration,
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"source_width": width,
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"source_height": height,
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"loaded_fps": 1/target_frame_time,
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"loaded_frame_count": len(images),
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"loaded_duration": len(images) * target_frame_time,
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"loaded_width": images.shape[2],
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"loaded_height": images.shape[1],
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}
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return (images, len(images), lazy_eval(audio), video_info)
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class ComfyUIDeployExternalVideo:
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@classmethod
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def INPUT_TYPES(s):
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input_dir = folder_paths.get_input_directory()
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files = []
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for f in os.listdir(input_dir):
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if os.path.isfile(os.path.join(input_dir, f)):
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file_parts = f.split('.')
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if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
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files.append(f)
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return {"required": {
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"input_id": (
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"STRING",
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{"multiline": False, "default": "input_video"},
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),
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"force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
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"force_size": (["Disabled", "Custom Height", "Custom Width", "Custom", "256x?", "?x256", "256x256", "512x?", "?x512", "512x512"],),
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"custom_width": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
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"custom_height": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
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"frame_load_cap": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
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"skip_first_frames": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
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"select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
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},
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"optional": {
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"meta_batch": ("VHS_BatchManager",),
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"default_value": (sorted(files),),
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},
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"hidden": {
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"unique_id": "UNIQUE_ID"
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},
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}
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CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
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RETURN_TYPES = ("IMAGE", "INT", "VHS_AUDIO", "VHS_VIDEOINFO",)
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RETURN_NAMES = ("IMAGE", "frame_count", "audio", "video_info",)
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FUNCTION = "load_video"
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def load_video(self, **kwargs):
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input_id = kwargs.get('input_id')
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force_rate = kwargs.get('force_rate')
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force_size = kwargs.get('force_size', "Disabled")
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custom_width = kwargs.get('custom_width')
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custom_height = kwargs.get('custom_height')
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frame_load_cap = kwargs.get('frame_load_cap')
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skip_first_frames = kwargs.get('skip_first_frames')
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select_every_nth = kwargs.get('select_every_nth')
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meta_batch = kwargs.get('meta_batch')
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unique_id = kwargs.get('unique_id')
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video = kwargs.get('default_value')
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video_path = folder_paths.get_annotated_filepath(video.strip("\""))
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input_dir = folder_paths.get_input_directory()
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if input_id.startswith('http'):
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import requests
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print("Fetching video from URL: ", input_id)
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response = requests.get(input_id, stream=True)
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file_size = int(response.headers.get('Content-Length', 0))
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file_extension = input_id.split('.')[-1].split('?')[0] # Extract extension and handle URLs with parameters
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if file_extension not in video_extensions:
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file_extension = ".mp4"
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unique_filename = str(uuid.uuid4()) + "." + file_extension
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video_path = os.path.join(input_dir, unique_filename)
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chunk_size = 1024 # 1 Kibibyte
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num_bars = int(file_size / chunk_size)
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with open(video_path, 'wb') as out_file:
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for chunk in tqdm(
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response.iter_content(chunk_size=chunk_size),
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total=num_bars,
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unit='KB',
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desc="Downloading",
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leave=True
|
|
):
|
|
out_file.write(chunk)
|
|
print("Video downloaded to: ", video_path)
|
|
|
|
print("video path: ", video_path)
|
|
|
|
return load_video_cv(video=video_path, force_rate=force_rate, force_size=force_size,
|
|
custom_width=custom_width, custom_height=custom_height, frame_load_cap=frame_load_cap,
|
|
skip_first_frames=skip_first_frames, select_every_nth=select_every_nth,
|
|
meta_batch=meta_batch, unique_id=unique_id)
|
|
|
|
@classmethod
|
|
def IS_CHANGED(s, video, **kwargs):
|
|
image_path = folder_paths.get_annotated_filepath(video)
|
|
return calculate_file_hash(image_path)
|
|
|
|
|
|
# class ComfyUIDeployExternalVideo:
|
|
# @classmethod
|
|
# def INPUT_TYPES(s):
|
|
# files = input_video_files()
|
|
# return {
|
|
# "required": {
|
|
# "input_id": (
|
|
# "STRING",
|
|
# {"multiline": False, "default": "input_video"},
|
|
# ),
|
|
# },
|
|
# "optional": {
|
|
# "default_value": (sorted(files),),
|
|
# }
|
|
# }
|
|
|
|
# RETURN_TYPES = (sorted(input_video_files()),)
|
|
# RETURN_NAMES = ("video_path",)
|
|
|
|
# FUNCTION = "run"
|
|
|
|
# CATEGORY = "deploy"
|
|
|
|
# def run(self, input_id, default_value=None):
|
|
# print("starting here?")
|
|
# input_dir = folder_paths.get_input_directory()
|
|
# if input_id.startswith('http'):
|
|
# import requests
|
|
# print("Fetching video from URL: ", input_id)
|
|
# response = requests.get(input_id, stream=True)
|
|
# file_size = int(response.headers.get('Content-Length', 0))
|
|
# file_extension = input_id.split('.')[-1].split('?')[0] # Extract extension and handle URLs with parameters
|
|
# if file_extension not in video_extensions:
|
|
# file_extension = ".mp4"
|
|
|
|
# unique_filename = str(uuid.uuid4()) + "." + file_extension
|
|
# video_path = os.path.join(input_dir, unique_filename)
|
|
# chunk_size = 1024 # 1 Kibibyte
|
|
|
|
# num_bars = int(file_size / chunk_size)
|
|
|
|
# with open(video_path, 'wb') as out_file:
|
|
# for chunk in tqdm(
|
|
# response.iter_content(chunk_size=chunk_size),
|
|
# total=num_bars,
|
|
# unit='KB',
|
|
# desc="Downloading",
|
|
# leave=True
|
|
# ):
|
|
# out_file.write(chunk)
|
|
# print("returning unique_filename: ", unique_filename)
|
|
# return (unique_filename,)
|
|
|
|
# print("returning default_value: ", default_value)
|
|
# return (default_value,)
|
|
|
|
|
|
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalVideo": ComfyUIDeployExternalVideo}
|
|
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalVideo": "External Video (ComfyUI Deploy)"}
|