vid node
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				@ -1,46 +1,434 @@
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import folder_paths
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					# credit goes to VHS
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import os
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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 uuid
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					import server
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from tqdm import tqdm
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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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					video_extensions = ['webm', 'mp4', 'mkv', 'gif']
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def input_video_files():
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    input_dir = folder_paths.get_input_directory()
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					def is_gif(filename) -> bool:
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    files = []
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					    file_parts = filename.split('.')
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    for f in os.listdir(input_dir):
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					    return len(file_parts) > 1 and file_parts[-1] == "gif"
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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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					def target_size(width, height, force_size, custom_width, custom_height) -> tuple[int, int]:
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                files.append(f)
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					    if force_size == "Custom":
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    return files
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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
 | 
				
			||||||
 | 
					    while video_cap.isOpened():
 | 
				
			||||||
 | 
					        if time_offset < target_frame_time:
 | 
				
			||||||
 | 
					            is_returned = video_cap.grab()
 | 
				
			||||||
 | 
					            # if didn't return frame, video has ended
 | 
				
			||||||
 | 
					            if not is_returned:
 | 
				
			||||||
 | 
					                break
 | 
				
			||||||
 | 
					            time_offset += base_frame_time
 | 
				
			||||||
 | 
					        if time_offset < target_frame_time:
 | 
				
			||||||
 | 
					            continue
 | 
				
			||||||
 | 
					        time_offset -= target_frame_time
 | 
				
			||||||
 | 
					        # if not at start_index, skip doing anything with frame
 | 
				
			||||||
 | 
					        total_frame_count += 1
 | 
				
			||||||
 | 
					        if total_frame_count <= skip_first_frames:
 | 
				
			||||||
 | 
					            continue
 | 
				
			||||||
 | 
					        else:
 | 
				
			||||||
 | 
					            total_frames_evaluated += 1
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					        # if should not be selected, skip doing anything with frame
 | 
				
			||||||
 | 
					        if total_frames_evaluated%select_every_nth != 0:
 | 
				
			||||||
 | 
					            continue
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					        # opencv loads images in BGR format (yuck), so need to convert to RGB for ComfyUI use
 | 
				
			||||||
 | 
					        # follow up: can videos ever have an alpha channel?
 | 
				
			||||||
 | 
					        # To my testing: No. opencv has no support for alpha
 | 
				
			||||||
 | 
					        unused, frame = video_cap.retrieve()
 | 
				
			||||||
 | 
					        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
 | 
				
			||||||
 | 
					        # convert frame to comfyui's expected format
 | 
				
			||||||
 | 
					        # TODO: frame contains no exif information. Check if opencv2 has already applied
 | 
				
			||||||
 | 
					        frame = np.array(frame, dtype=np.float32) / 255.0
 | 
				
			||||||
 | 
					        if prev_frame is not None:
 | 
				
			||||||
 | 
					            inp  = yield prev_frame
 | 
				
			||||||
 | 
					            if inp is not None:
 | 
				
			||||||
 | 
					                #ensure the finally block is called
 | 
				
			||||||
 | 
					                return
 | 
				
			||||||
 | 
					        prev_frame = frame
 | 
				
			||||||
 | 
					        frames_added += 1
 | 
				
			||||||
 | 
					        # if cap exists and we've reached it, stop processing frames
 | 
				
			||||||
 | 
					        if frame_load_cap > 0 and frames_added >= frame_load_cap:
 | 
				
			||||||
 | 
					            break
 | 
				
			||||||
 | 
					    if meta_batch is not None:
 | 
				
			||||||
 | 
					        meta_batch.inputs.pop(unique_id)
 | 
				
			||||||
 | 
					        meta_batch.has_closed_inputs = True
 | 
				
			||||||
 | 
					    if prev_frame is not None:
 | 
				
			||||||
 | 
					        yield prev_frame
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					def load_video_cv(video: str, force_rate: int, force_size: str,
 | 
				
			||||||
 | 
					                  custom_width: int,custom_height: int, frame_load_cap: int,
 | 
				
			||||||
 | 
					                  skip_first_frames: int, select_every_nth: int,
 | 
				
			||||||
 | 
					                  meta_batch=None, unique_id=None):
 | 
				
			||||||
 | 
					    if meta_batch is None or unique_id not in meta_batch.inputs:
 | 
				
			||||||
 | 
					        gen = cv_frame_generator(video, force_rate, frame_load_cap, skip_first_frames,
 | 
				
			||||||
 | 
					                                 select_every_nth, meta_batch, unique_id)
 | 
				
			||||||
 | 
					        (width, height, fps, duration, total_frames, target_frame_time) = next(gen)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					        if meta_batch is not None:
 | 
				
			||||||
 | 
					            meta_batch.inputs[unique_id] = (gen, width, height, fps, duration, total_frames, target_frame_time)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    else:
 | 
				
			||||||
 | 
					        (gen, width, height, fps, duration, total_frames, target_frame_time) = meta_batch.inputs[unique_id]
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    if meta_batch is not None:
 | 
				
			||||||
 | 
					        gen = itertools.islice(gen, meta_batch.frames_per_batch)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    #Some minor wizardry to eliminate a copy and reduce max memory by a factor of ~2
 | 
				
			||||||
 | 
					    images = torch.from_numpy(np.fromiter(gen, np.dtype((np.float32, (height, width, 3)))))
 | 
				
			||||||
 | 
					    if len(images) == 0:
 | 
				
			||||||
 | 
					        raise RuntimeError("No frames generated")
 | 
				
			||||||
 | 
					    if force_size != "Disabled":
 | 
				
			||||||
 | 
					        new_size = target_size(width, height, force_size, custom_width, custom_height)
 | 
				
			||||||
 | 
					        if new_size[0] != width or new_size[1] != height:
 | 
				
			||||||
 | 
					            s = images.movedim(-1,1)
 | 
				
			||||||
 | 
					            s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
 | 
				
			||||||
 | 
					            images = s.movedim(1,-1)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    #Setup lambda for lazy audio capture
 | 
				
			||||||
 | 
					    audio = lambda : get_audio(video, skip_first_frames * target_frame_time,
 | 
				
			||||||
 | 
					                               frame_load_cap*target_frame_time*select_every_nth)
 | 
				
			||||||
 | 
					    #Adjust target_frame_time for select_every_nth
 | 
				
			||||||
 | 
					    target_frame_time *= select_every_nth
 | 
				
			||||||
 | 
					    video_info = {
 | 
				
			||||||
 | 
					        "source_fps": fps,
 | 
				
			||||||
 | 
					        "source_frame_count": total_frames,
 | 
				
			||||||
 | 
					        "source_duration": duration,
 | 
				
			||||||
 | 
					        "source_width": width,
 | 
				
			||||||
 | 
					        "source_height": height,
 | 
				
			||||||
 | 
					        "loaded_fps": 1/target_frame_time,
 | 
				
			||||||
 | 
					        "loaded_frame_count": len(images),
 | 
				
			||||||
 | 
					        "loaded_duration": len(images) * target_frame_time,
 | 
				
			||||||
 | 
					        "loaded_width": images.shape[2],
 | 
				
			||||||
 | 
					        "loaded_height": images.shape[1],
 | 
				
			||||||
 | 
					    }
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    return (images, len(images), lazy_eval(audio), video_info)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					
 | 
				
			||||||
class ComfyUIDeployExternalVideo:
 | 
					class ComfyUIDeployExternalVideo:
 | 
				
			||||||
    @classmethod
 | 
					    @classmethod
 | 
				
			||||||
    def INPUT_TYPES(s):
 | 
					    def INPUT_TYPES(s):
 | 
				
			||||||
        files = input_video_files()
 | 
					        input_dir = folder_paths.get_input_directory()
 | 
				
			||||||
        return {
 | 
					        files = []
 | 
				
			||||||
            "required": {
 | 
					        for f in os.listdir(input_dir):
 | 
				
			||||||
                "input_id": (
 | 
					            if os.path.isfile(os.path.join(input_dir, f)):
 | 
				
			||||||
                    "STRING",
 | 
					                file_parts = f.split('.')
 | 
				
			||||||
                    {"multiline": False, "default": "input_video"},
 | 
					                if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
 | 
				
			||||||
                ),
 | 
					                    files.append(f)
 | 
				
			||||||
            },
 | 
					        return {"required": {
 | 
				
			||||||
            "optional": {
 | 
					                    "input_id": (
 | 
				
			||||||
                "default_value": (sorted(files),),
 | 
					                        "STRING",
 | 
				
			||||||
            }
 | 
					                        {"multiline": False, "default": "input_video"},
 | 
				
			||||||
        }
 | 
					                    ),
 | 
				
			||||||
 | 
					                     "force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
 | 
				
			||||||
 | 
					                     "force_size": (["Disabled", "Custom Height", "Custom Width", "Custom", "256x?", "?x256", "256x256", "512x?", "?x512", "512x512"],),
 | 
				
			||||||
 | 
					                     "custom_width": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
 | 
				
			||||||
 | 
					                     "custom_height": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
 | 
				
			||||||
 | 
					                     "frame_load_cap": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
 | 
				
			||||||
 | 
					                     "skip_first_frames": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
 | 
				
			||||||
 | 
					                     "select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
 | 
				
			||||||
 | 
					                     },
 | 
				
			||||||
 | 
					                "optional": {
 | 
				
			||||||
 | 
					                    "meta_batch": ("VHS_BatchManager",),
 | 
				
			||||||
 | 
					                    "default_value": (sorted(files),),
 | 
				
			||||||
 | 
					                },
 | 
				
			||||||
 | 
					                "hidden": {
 | 
				
			||||||
 | 
					                    "unique_id": "UNIQUE_ID"
 | 
				
			||||||
 | 
					                },
 | 
				
			||||||
 | 
					                }
 | 
				
			||||||
 | 
					
 | 
				
			||||||
    RETURN_TYPES = (sorted(input_video_files()),)
 | 
					    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
 | 
				
			||||||
    RETURN_NAMES = ("video_path",)
 | 
					 | 
				
			||||||
 | 
					
 | 
				
			||||||
    FUNCTION = "run"
 | 
					    RETURN_TYPES = ("IMAGE", "INT", "VHS_AUDIO", "VHS_VIDEOINFO",)
 | 
				
			||||||
 | 
					    RETURN_NAMES = ("IMAGE", "frame_count", "audio", "video_info",)
 | 
				
			||||||
 | 
					
 | 
				
			||||||
    CATEGORY = "deploy"
 | 
					    FUNCTION = "load_video"
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					    def load_video(self, **kwargs):
 | 
				
			||||||
 | 
					        input_id = kwargs.get('input_id')
 | 
				
			||||||
 | 
					        force_rate = kwargs.get('force_rate')
 | 
				
			||||||
 | 
					        force_size = kwargs.get('force_size', "Disabled")
 | 
				
			||||||
 | 
					        custom_width = kwargs.get('custom_width')
 | 
				
			||||||
 | 
					        custom_height = kwargs.get('custom_height')
 | 
				
			||||||
 | 
					        frame_load_cap = kwargs.get('frame_load_cap')
 | 
				
			||||||
 | 
					        skip_first_frames = kwargs.get('skip_first_frames')
 | 
				
			||||||
 | 
					        select_every_nth = kwargs.get('select_every_nth')
 | 
				
			||||||
 | 
					        meta_batch = kwargs.get('meta_batch')
 | 
				
			||||||
 | 
					        unique_id = kwargs.get('unique_id')
 | 
				
			||||||
 | 
					
 | 
				
			||||||
 | 
					        video = kwargs.get('default_value')
 | 
				
			||||||
 | 
					        video_path = folder_paths.get_annotated_filepath(video.strip("\""))
 | 
				
			||||||
 | 
					
 | 
				
			||||||
    def run(self, input_id, default_value=None):
 | 
					 | 
				
			||||||
        print("starting here?")
 | 
					 | 
				
			||||||
        input_dir = folder_paths.get_input_directory()
 | 
					        input_dir = folder_paths.get_input_directory()
 | 
				
			||||||
        if input_id.startswith('http'):
 | 
					        if input_id.startswith('http'):
 | 
				
			||||||
            import requests
 | 
					            import requests
 | 
				
			||||||
@ -66,11 +454,76 @@ class ComfyUIDeployExternalVideo:
 | 
				
			|||||||
                    leave=True 
 | 
					                    leave=True 
 | 
				
			||||||
                ):
 | 
					                ):
 | 
				
			||||||
                    out_file.write(chunk)
 | 
					                    out_file.write(chunk)
 | 
				
			||||||
            print("returning unique_filename: ", unique_filename)
 | 
					            print("Video downloaded to: ", video_path)
 | 
				
			||||||
            return (unique_filename,)
 | 
					 | 
				
			||||||
        
 | 
					        
 | 
				
			||||||
        print("returning default_value: ", default_value)
 | 
					        print("video path: ", video_path)
 | 
				
			||||||
        return (default_value,)
 | 
					
 | 
				
			||||||
 | 
					        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_CLASS_MAPPINGS = {"ComfyUIDeployExternalVideo": ComfyUIDeployExternalVideo}
 | 
				
			||||||
 | 
				
			|||||||
@ -1,2 +1,4 @@
 | 
				
			|||||||
aiofiles
 | 
					aiofiles
 | 
				
			||||||
pydantic
 | 
					pydantic
 | 
				
			||||||
 | 
					opencv-python
 | 
				
			||||||
 | 
					imageio-ffmpeg
 | 
				
			||||||
		Loading…
	
	
			
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		Reference in New Issue
	
	Block a user