# Documentation - Class name: LoadVideoFromUrl - Category: Art Venture/Loaders - Output node: False LoadVideoFromUrl节点旨在从URL加载视频内容，并将其转换为适合进一步处理或分析的格式。它支持处理各种URL格式，包括视频文件的直接链接，并将其转换为系统内使用的标准化视频格式。 # Input types ## Required - video - "video"参数是一个字符串，表示要加载的视频的URL。它在确定视频获取和处理的来源方面起着关键作用。 - Comfy dtype: STRING - Python dtype: str - force_rate - 指定加载视频的目标帧率，允许控制播放速度或帧率标准化。 - Comfy dtype: INT - Python dtype: Optional[float] - force_size - 定义加载视频的目标分辨率，实现调整大小或纵横比。 - Comfy dtype: COMBO[STRING] - Python dtype: Optional[str] - custom_width - 为加载的视频设置自定义宽度，覆盖默认或指定的'force_size'宽度。 - Comfy dtype: INT - Python dtype: Optional[int] - custom_height - 为加载的视频设置自定义高度，覆盖默认或指定的'force_size'高度。 - Comfy dtype: INT - Python dtype: Optional[int] - frame_load_cap - 限制从视频中加载的帧数，适用于处理长视频或采样。 - Comfy dtype: INT - Python dtype: Optional[int] - skip_first_frames - 跳过视频开头指定数量的帧，用于跳过不需要的内容或片头。 - Comfy dtype: INT - Python dtype: Optional[int] - select_every_nth - 从视频中加载每第n帧，允许降低帧率或选择性帧分析。 - Comfy dtype: INT - Python dtype: Optional[int] ## Optional - meta_batch - 启用加载视频的元数据批处理，优化视频元数据至关重要的场景。 - Comfy dtype: VHS_BatchManager - Python dtype: Optional[bool] # Output types - frames - 表示加载视频的张量列表。 - Comfy dtype: IMAGE - Python dtype: List[torch.Tensor] - frame_count - 包含每个加载视频的帧数的列表。 - Comfy dtype: INT - Python dtype: List[int] - has_video - 指示是否成功加载任何视频的布尔值。 - Comfy dtype: BOOLEAN - Python dtype: bool ## Usage tips - Infra type: `CPU` - Common nodes: unknown ## Source code ```python class UtilLoadVideoFromUrl(LoadVideoPath): @classmethod def INPUT_TYPES(s): inputs = LoadVideoPath.INPUT_TYPES() inputs["required"]["video"] = ("STRING", {"default": "", "multiline": True, "dynamicPrompts": False}) return inputs CATEGORY = "Art Venture/Loaders" FUNCTION = "load" RETURN_TYPES = ("IMAGE", "INT", "BOOLEAN") RETURN_NAMES = ("frames", "frame_count", "has_video") OUTPUT_IS_LIST = (True, True, False) def load_gif( self, gif_path: str, force_rate: int, force_size: str, skip_first_frames: int, frame_load_cap: int, select_every_nth: int, ): from PIL import Image, ImageSequence image = Image.open(gif_path) frames = [] total_frames_evaluated = -1 if force_rate != 0: print(f"Force rate is not supported for gifs/webps") if frame_load_cap == 0: frame_load_cap = 999999999 for i, frame in enumerate(ImageSequence.Iterator(image)): if i < skip_first_frames: continue elif i >= skip_first_frames + frame_load_cap: break else: total_frames_evaluated += 1 if total_frames_evaluated % select_every_nth == 0: frames.append(pil2tensor(frame.copy().convert("RGB"))) images = torch.cat(frames, dim=0) if force_size != "Disabled": height = images.shape[1] width = images.shape[2] new_size = target_size(width, height, force_size) 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", "disabled") images = s.movedim(1, -1) return (images, len(frames)) def load_url(self, video: str, **kwargs): url = video.strip('"') if url == "": return (None, 0) if os.path.isfile(url): pass elif url.startswith("file://"): url = url[7:] url = os.path.abspath(url) if not os.path.isfile(url): raise Exception(f"File {url} does not exist") if url.startswith(input_dir): video = url[len(input_dir) + 1 :] + " [input]" elif url.startswith(output_dir): video = url[len(output_dir) + 1 :] + " [output]" elif url.startswith(temp_dir): video = url[len(temp_dir) + 1 :] + " [temp]" else: # move file to temp_dir import shutil tempdir = os.path.join(temp_dir, "video") if not os.path.exists(tempdir): os.makedirs(tempfile, exist_ok=True) filename = os.path.basename(url) filepath = os.path.join(tempdir, filename) i = 1 split = os.path.splitext(filename) while os.path.exists(filepath): filename = f"{split[0]} ({i}){split[1]}" filepath = os.path.join(tempdir, filename) i += 1 shutil.copy(url, filepath) video = "video/" + filename + " [temp]" elif url.startswith("http://") or url.startswith("https://"): from torch.hub import download_url_to_file from urllib.parse import urlparse parts = urlparse(url) filename = os.path.basename(parts.path) tempfile = os.path.join(temp_dir, "video") if not os.path.exists(tempfile): os.makedirs(tempfile, exist_ok=True) tempfile = os.path.join(tempfile, filename) print(f'Downloading: "{url}" to {tempfile}\n') download_url_to_file(url, tempfile, progress=True) video = "video/" + filename + " [temp]" elif url.startswith("/view?"): from urllib.parse import parse_qs qs = parse_qs(url[6:]) filename = qs.get("name", qs.get("filename", None)) if filename is None: raise Exception(f"Invalid url: {url}") filename = filename[0] subfolder = qs.get("subfolder", None) if subfolder is not None: filename = os.path.join(subfolder[0], filename) dirtype = qs.get("type", ["input"]) video = f"{filename} [{dirtype[0]}]" else: raise Exception(f"Invalid url: {url}") if ".gif [" in video.lower() or ".webp [" in video.lower(): gif_path = folder_paths.get_annotated_filepath(video.strip('"')) res = self.load_gif(gif_path, **kwargs) else: res = self.load_video(video=video, **kwargs) return res def load(self, video: str, **kwargs): urls = video.strip().split("\n") videos = [] frame_counts = [] for url in urls: images, frame_count = self.load_url(url, **kwargs) if images is not None and frame_count > 0: videos.append(images) frame_counts.append(frame_count) has_video = len(videos) > 0 if not has_video: image = torch.zeros((1, 64, 64, 3), dtype=torch.float32, device="cpu") videos.append(image) frame_counts.append(1) return (videos, frame_counts, has_video) @classmethod def IS_CHANGED(s, video: str, **kwargs): return video @classmethod def VALIDATE_INPUTS(s, **kwargs): return True ```