DiffIR2VR / utils /video_visualizer.py
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import os.path
from skvideo.io import FFmpegWriter
# from image_utils import parse_image_size
# from image_utils import load_image
# from image_utils import resize_image
# from image_utils import list_images_from_dir
from .image_utils import parse_image_size
from .image_utils import load_image
from .image_utils import resize_image
from .image_utils import list_images_from_dir
class VideoVisualizer(object):
"""Defines the video visualizer that presents images as a video."""
def __init__(self,
path=None,
frame_size=None,
fps=25.0,
codec='libx264',
pix_fmt='yuv420p',
crf=1):
"""Initializes the video visualizer.
Args:
path: Path to write the video. (default: None)
frame_size: Frame size, i.e., (height, width). (default: None)
fps: Frames per second. (default: 24)
codec: Codec. (default: `libx264`)
pix_fmt: Pixel format. (default: `yuv420p`)
crf: Constant rate factor, which controls the compression. The
larger this field is, the higher compression and lower quality.
`0` means no compression and consequently the highest quality.
To enable QuickTime playing (requires YUV to be 4:2:0, but
`crf = 0` results YUV to be 4:4:4), please set this field as
at least 1. (default: 1)
"""
self.set_path(path)
self.set_frame_size(frame_size)
self.set_fps(fps)
self.set_codec(codec)
self.set_pix_fmt(pix_fmt)
self.set_crf(crf)
self.video = None
def set_path(self, path=None):
"""Sets the path to save the video."""
self.path = path
def set_frame_size(self, frame_size=None):
"""Sets the video frame size."""
height, width = parse_image_size(frame_size)
self.frame_height = height
self.frame_width = width
def set_fps(self, fps=25.0):
"""Sets the FPS (frame per second) of the video."""
self.fps = fps
def set_codec(self, codec='libx264'):
"""Sets the video codec."""
self.codec = codec
def set_pix_fmt(self, pix_fmt='yuv420p'):
"""Sets the video pixel format."""
self.pix_fmt = pix_fmt
def set_crf(self, crf=1):
"""Sets the CRF (constant rate factor) of the video."""
self.crf = crf
def init_video(self):
"""Initializes an empty video with expected settings."""
assert self.frame_height > 0
assert self.frame_width > 0
video_setting = {
'-r': f'{self.fps:.2f}',
'-s': f'{self.frame_width}x{self.frame_height}',
'-vcodec': f'{self.codec}',
'-crf': f'{self.crf}',
'-pix_fmt': f'{self.pix_fmt}',
}
self.video = FFmpegWriter(self.path, outputdict=video_setting)
def add(self, frame):
"""Adds a frame into the video visualizer.
NOTE: The input frame is assumed to be with `RGB` channel order.
"""
if self.video is None:
height, width = frame.shape[0:2]
if height & 1:
height -= 1
if width & 1:
width -= 1
# height = self.frame_height or height
# width = self.frame_width or width
self.set_frame_size((height, width))
self.init_video()
if frame.shape[0:2] != (self.frame_height, self.frame_width):
frame = resize_image(frame, (self.frame_width, self.frame_height))
self.video.writeFrame(frame)
def visualize_collection(self, images, save_path=None):
"""Visualizes a collection of images one by one."""
if save_path is not None and save_path != self.path:
self.save()
self.set_path(save_path)
for image in images:
self.add(image)
self.save()
def visualize_list(self, image_list, save_path=None):
"""Visualizes a list of image files."""
if save_path is not None and save_path != self.path:
self.save()
self.set_path(save_path)
for filename in image_list:
image = load_image(filename)
self.add(image)
self.save()
def visualize_directory(self, directory, save_path=None):
"""Visualizes all images under a directory."""
image_list = list_images_from_dir(directory)
self.visualize_list(image_list, save_path)
def save(self):
"""Saves the video by closing the file."""
if self.video is not None:
self.video.close()
self.video = None
self.set_path(None)
if __name__ == '__main__':
from glob import glob
import cv2
video_visualizer = VideoVisualizer(path='/home/yehhh/DiffBIR/DAVIS_bear.mp4',
frame_size=None,
fps=25.0)
img_folder = "/home/yehhh/DiffBIR/inputs/bear"
imgs = sorted(glob(img_folder + '/*.png'))
imgs = sorted(glob(img_folder + '/*.jpg'))
for img in imgs:
image = cv2.imread(img)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
video_visualizer.add(image)
video_visualizer.save()