Initial commit: ComfyUI Video Compressor node
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Verolelb
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MIT License
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Copyright (c) 2023 [VOTRE NOM OU PSEUDO]
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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\# ComfyUI Video Compressor Node
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Un node personnalisé pour ComfyUI qui permet de compresser des fichiers vidéo en utilisant FFmpeg, en visant une taille de fichier cible spécifique.
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<!-- Mettez une capture d'écran ici ! -->
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\## 🌟 Fonctionnalités
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\- \*\*Entrée Vidéo Simple\*\* : Prend en entrée un chemin vers un fichier vidéo (parfait pour être chaîné après un node "Video Combine").
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\- \*\*Contrôle de la Taille\*\* : Un slider simple pour définir le poids final souhaité de la vidéo en Mégaoctets (MB).
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\- \*\*Choix du Codec\*\* : Choisissez entre `libx264` (H.264, très compatible) et `libx265` (H.265/HEVC, plus efficace).
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\- \*\*Sortie Organisée\*\* : Les vidéos compressées sont sauvegardées dans `ComfyUI/output/compressed\_videos/`.
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\## ⚙️ Installation
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\### 1. Prérequis : FFmpeg
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\*\*Ce node nécessite que FFmpeg soit installé sur votre système et accessible depuis le terminal.\*\*
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\- \*\*Windows\*\* : Téléchargez depuis \[gyan.dev](https://www.gyan.dev/ffmpeg/builds/) et suivez un tutoriel pour ajouter le dossier `bin` à votre variable d'environnement PATH.
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\- \*\*MacOS\*\* : Installez avec Homebrew : `brew install ffmpeg`
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\- \*\*Linux\*\* : Utilisez votre gestionnaire de paquets : `sudo apt update \&\& sudo apt install ffmpeg`
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Pour vérifier que l'installation a réussi, ouvrez un terminal et tapez `ffmpeg -version`. Vous devriez voir les informations de version s'afficher.
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\### 2. Installation du Node
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La méthode la plus simple est d'utiliser `git`.
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1\. Ouvrez un terminal.
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2\. Naviguez jusqu'au répertoire des nodes personnalisés de ComfyUI : `cd ComfyUI/custom\_nodes/`
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3\. Clonez ce dépôt : `git clone https://github.com/VOTRE\_NOM\_UTILISATEUR/ComfyUI-VideoCompressor.git` <!-- REMPLACEZ PAR VOTRE URL GITHUB -->
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4\. Redémarrez ComfyUI.
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Le node devrait maintenant apparaître dans le menu "Add Node" sous la catégorie `🎥Video Utils`.
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\## 🚀 Utilisation
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1\. Générez une séquence d'images et combinez-les en une vidéo avec un node comme "Video Combine".
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2\. Connectez la sortie `video` (le chemin du fichier) de ce node à l'entrée `video` du node `🎬 Compress Video (FFmpeg)`.
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3\. Ajustez le slider `target\_mb` à la taille désirée (par ex. 8 MB pour Discord).
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4\. Lancez le workflow. La vidéo compressée sera disponible à la sortie `compressed\_video\_path` et sera enregistrée sur votre disque.
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\## 📄 Licence
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Ce projet est sous licence MIT. Voir le fichier `LICENSE` pour plus de détails.
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# On importe le nom correct de la classe : "VideoCompressorUnified"
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from .compress_video_node import VideoCompressorUnified
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NODE_CLASS_MAPPINGS = {
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# On utilise le même nom ici
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"VideoCompressorUnified": VideoCompressorUnified
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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# Et ici, pour le nom affiché dans le menu
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"VideoCompressorUnified": "🎬 Compress Video (Unified)"
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}
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print("✅ ComfyUI-VideoCompressor: Node unifié chargé.")
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import os
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import subprocess
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import folder_paths
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import torch
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import numpy as np
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from PIL import Image
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import shutil
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import datetime
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import platform
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class VideoCompressorUnified:
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"""
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Node de compression vidéo unifié :
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- Accepte images ou vidéo
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- Trois modes : fast_crf, 2pass, gpu
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"""
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"mode": (["fast_crf", "2pass", "gpu"], {"default": "2pass"}),
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"target_mb": ("FLOAT", {"min": 0.5, "max": 2000.0, "step": 0.5, "default": 8.0}),
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"codec": (["libx264", "libx265", "h264_nvenc", "hevc_nvenc"], {"default": "libx264"}),
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},
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"optional": {
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"images": ("IMAGE",),
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"video_path_in": ("STRING", {"forceInput": True}),
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"fps": ("INT", {"default": 24, "min": 1, "max": 60}),
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"crf": ("INT", {"default": 23, "min": 10, "max": 40}),
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"preset": ([
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"ultrafast","superfast","veryfast","faster",
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"fast","medium","slow","slower","veryslow"
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], {"default": "fast"}),
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}
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}
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RETURN_TYPES = ("STRING", "IMAGE")
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RETURN_NAMES = ("video_path_out", "images")
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FUNCTION = "process"
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CATEGORY = "🎥Video Utils"
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def _get_video_info(self, video_path):
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command = [
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"ffprobe", "-v", "error", "-select_streams", "v:0",
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"-show_entries", "stream=r_frame_rate,duration",
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"-of", "csv=p=0", video_path
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]
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result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, check=True)
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parts = result.stdout.strip().split(',')
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if len(parts) < 2:
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raise ValueError("Impossible d'analyser la vidéo.")
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fps_fraction = parts[0].split('/')
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fps = float(fps_fraction[0]) / float(fps_fraction[1]) if len(fps_fraction) == 2 else 30.0
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duration = float(parts[1])
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return {"duration": duration, "fps": fps}
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def _load_video_to_tensor(self, video_path, temp_dir):
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frames_dir = os.path.join(temp_dir, "loaded_frames")
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os.makedirs(frames_dir, exist_ok=True)
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subprocess.run(
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["ffmpeg", "-i", video_path, os.path.join(frames_dir, "frame_%05d.png")],
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check=True, capture_output=True
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)
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frame_files = sorted([os.path.join(frames_dir, f) for f in os.listdir(frames_dir) if f.endswith('.png')])
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images = [torch.from_numpy(np.array(Image.open(f).convert("RGB")).astype(np.float32) / 255.0).unsqueeze(0) for f in frame_files]
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if not images:
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return torch.empty(0)
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return torch.cat(images, 0)
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def process(self, mode, target_mb, codec, images=None, video_path_in=None, fps=24, crf=23, preset="fast"):
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if images is None and video_path_in is None:
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return ("", torch.empty(0))
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temp_dir = os.path.join(folder_paths.get_temp_directory(), "compressor_unified")
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shutil.rmtree(temp_dir, ignore_errors=True)
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os.makedirs(temp_dir, exist_ok=True)
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pass_log_file = os.path.join(temp_dir, "ffmpeg_passlog")
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try:
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if images is not None:
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output_images = images
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for i, img_tensor in enumerate(images):
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Image.fromarray((255. * img_tensor.cpu().numpy()).astype(np.uint8)).save(os.path.join(temp_dir, f"frame_{i:05d}.png"))
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initial_video_path = os.path.join(temp_dir, "initial_from_images.mp4")
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subprocess.run(
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["ffmpeg", "-y", "-framerate", str(fps), "-i", os.path.join(temp_dir, "frame_%05d.png"),
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"-c:v", "libx264", "-pix_fmt", "yuv420p", initial_video_path],
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check=True, capture_output=True
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)
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else:
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if not os.path.exists(video_path_in):
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raise FileNotFoundError(f"Fichier vidéo non trouvé: {video_path_in}")
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initial_video_path = video_path_in
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output_images = self._load_video_to_tensor(video_path_in, temp_dir)
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output_dir = os.path.join(folder_paths.get_output_directory(), "compressed_videos")
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os.makedirs(output_dir, exist_ok=True)
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timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
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filename = f"compressed_{timestamp}.mp4"
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final_video_path = os.path.join(output_dir, filename)
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info = self._get_video_info(initial_video_path)
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duration_s = info["duration"]
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if duration_s <= 0:
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raise ValueError("Durée de la vidéo nulle ou invalide.")
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# ----- Choix du mode -----
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if mode == "2pass":
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# Calcule le bitrate cible
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target_size_bits = target_mb * 1024 * 1024 * 8
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audio_bitrate_bits = 128 * 1000
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video_bitrate_bits = (target_size_bits / duration_s) - audio_bitrate_bits
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if video_bitrate_bits < 100 * 1000:
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video_bitrate_bits = 100 * 1000
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video_bitrate_k = int(video_bitrate_bits / 1000)
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null_output = "NUL" if platform.system() == "Windows" else "/dev/null"
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common_args = ["-y", "-i", initial_video_path, "-c:v", codec, "-b:v", f"{video_bitrate_k}k", "-preset", preset, "-threads", "0"]
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# Première passe
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subprocess.run(["ffmpeg"] + common_args + ["-pass", "1", "-an", "-f", "mp4", "-passlogfile", pass_log_file, null_output], check=True, capture_output=True)
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# Deuxième passe
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subprocess.run(["ffmpeg"] + common_args + ["-pass", "2", "-c:a", "aac", "-b:a", "128k", "-passlogfile", pass_log_file, final_video_path], check=True, capture_output=True)
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elif mode == "fast_crf":
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subprocess.run([
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"ffmpeg", "-y", "-i", initial_video_path,
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"-c:v", codec, "-preset", preset, "-crf", str(crf),
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"-c:a", "aac", "-b:a", "128k", "-threads", "0",
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final_video_path
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], check=True, capture_output=True)
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elif mode == "gpu":
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# Ici on force un CRF rapide avec encodeur GPU
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subprocess.run([
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"ffmpeg", "-y", "-i", initial_video_path,
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"-c:v", codec, "-preset", preset, "-cq", str(crf),
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"-c:a", "aac", "-b:a", "128k", "-threads", "0",
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final_video_path
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], check=True, capture_output=True)
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else:
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raise ValueError(f"Mode inconnu: {mode}")
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return (final_video_path, output_images)
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finally:
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shutil.rmtree(temp_dir, ignore_errors=True)
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