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| # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
| # SPDX-License-Identifier: Apache-2.0 | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import json | |
| from io import BytesIO | |
| from typing import Dict, List | |
| import imageio | |
| import numpy as np | |
| def read_prompts_from_file(prompt_file: str) -> List[Dict[str, str]]: | |
| """Read prompts from a JSONL file where each line is a dict with 'prompt' key and optionally 'visual_input' key. | |
| Args: | |
| prompt_file (str): Path to JSONL file containing prompts | |
| Returns: | |
| List[Dict[str, str]]: List of prompt dictionaries | |
| """ | |
| prompts = [] | |
| with open(prompt_file, "r") as f: | |
| for line in f: | |
| prompt_dict = json.loads(line.strip()) | |
| prompts.append(prompt_dict) | |
| return prompts | |
| def save_video(video, fps, H, W, video_save_quality, video_save_path): | |
| """Save video frames to file. | |
| Args: | |
| grid (np.ndarray): Video frames array [T,H,W,C] | |
| fps (int): Frames per second | |
| H (int): Frame height | |
| W (int): Frame width | |
| video_save_quality (int): Video encoding quality (0-10) | |
| video_save_path (str): Output video file path | |
| """ | |
| kwargs = { | |
| "fps": fps, | |
| "quality": video_save_quality, | |
| "macro_block_size": 1, | |
| "ffmpeg_params": ["-s", f"{W}x{H}"], | |
| "output_params": ["-f", "mp4"], | |
| } | |
| imageio.mimsave(video_save_path, video, "mp4", **kwargs) | |
| def load_from_fileobj(filepath: str, format: str = "mp4", mode: str = "rgb", **kwargs): | |
| """ | |
| Load video from a file-like object using imageio with specified format and color mode. | |
| Parameters: | |
| file (IO[bytes]): A file-like object containing video data. | |
| format (str): Format of the video file (default 'mp4'). | |
| mode (str): Color mode of the video, 'rgb' or 'gray' (default 'rgb'). | |
| Returns: | |
| tuple: A tuple containing an array of video frames and metadata about the video. | |
| """ | |
| with open(filepath, "rb") as f: | |
| value = f.read() | |
| with BytesIO(value) as f: | |
| f.seek(0) | |
| video_reader = imageio.get_reader(f, format, **kwargs) | |
| video_frames = [] | |
| for frame in video_reader: | |
| if mode == "gray": | |
| import cv2 # Convert frame to grayscale if mode is gray | |
| frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) | |
| frame = np.expand_dims(frame, axis=2) # Keep frame dimensions consistent | |
| video_frames.append(frame) | |
| return np.array(video_frames), video_reader.get_meta_data() | |