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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.
from typing import IO
import numpy as np
import torch
from cosmos_predict1.utils.easy_io.handlers.base import BaseFileHandler
try:
import imageio
except ImportError:
imageio = None
class ImageioVideoHandler(BaseFileHandler):
str_like = False
def load_from_fileobj(self, file: IO[bytes], 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.
"""
file.seek(0)
video_reader = imageio.get_reader(file, 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()
def dump_to_fileobj(
self,
obj: np.ndarray | torch.Tensor,
file: IO[bytes],
format: str = "mp4", # pylint: disable=redefined-builtin
fps: int = 17,
quality: int = 5,
**kwargs,
):
"""
Save an array of video frames to a file-like object using imageio.
Parameters:
obj (np.ndarray): An array of frames to be saved as video.
file (IO[bytes]): A file-like object to which the video data will be written.
format (str): Format of the video file (default 'mp4').
fps (int): Frames per second of the output video (default 30).
"""
if isinstance(obj, torch.Tensor):
assert obj.dtype == torch.uint8
obj = obj.cpu().numpy()
h, w = obj.shape[1:-1]
kwargs = {
"fps": fps,
"quality": quality,
"macro_block_size": 1,
"ffmpeg_params": ["-s", f"{w}x{h}"],
"output_params": ["-f", "mp4"],
}
imageio.mimsave(file, obj, format, **kwargs)
def dump_to_str(self, obj, **kwargs):
raise NotImplementedError
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