Source code for moviepy.video.io.ImageSequenceClip
"""Implements ImageSequenceClip, a class to create a video clip from a set
of image files.
"""
import os
import numpy as np
from imageio.v2 import imread
from moviepy.video.VideoClip import VideoClip
[docs]
class ImageSequenceClip(VideoClip):
"""A VideoClip made from a series of images.
Parameters
----------
sequence
Can be one of these:
- The name of a folder (containing only pictures). The pictures
will be considered in alphanumerical order.
- A list of names of image files. In this case you can choose to
load the pictures in memory pictures
- A list of Numpy arrays representing images. In this last case,
masks are not supported currently.
fps
Number of picture frames to read per second. Instead, you can provide
the duration of each image with durations (see below)
durations
List of the duration of each picture.
with_mask
Should the alpha layer of PNG images be considered as a mask ?
is_mask
Will this sequence of pictures be used as an animated mask.
load_images
Specify that all images should be loaded into the RAM. This is only
interesting if you have a small number of images that will be used
more than once.
"""
def __init__(
self,
sequence,
fps=None,
durations=None,
with_mask=True,
is_mask=False,
load_images=False,
):
# CODE WRITTEN AS IT CAME, MAY BE IMPROVED IN THE FUTURE
if (fps is None) and (durations is None):
raise ValueError("Please provide either 'fps' or 'durations'.")
VideoClip.__init__(self, is_mask=is_mask)
# Parse the data
fromfiles = True
if isinstance(sequence, list):
if isinstance(sequence[0], str):
if load_images:
sequence = [imread(file) for file in sequence]
fromfiles = False
else:
fromfiles = True
else:
# sequence is already a list of numpy arrays
fromfiles = False
else:
# sequence is a folder name, make it a list of files:
fromfiles = True
sequence = sorted(
[os.path.join(sequence, file) for file in os.listdir(sequence)]
)
# check that all the images are of the same size
if isinstance(sequence[0], str):
size = imread(sequence[0]).shape
else:
size = sequence[0].shape
for image in sequence:
image1 = image
if isinstance(image, str):
image1 = imread(image)
if size != image1.shape:
raise Exception(
"MoviePy: ImageSequenceClip requires all images to be the same size"
)
self.fps = fps
if fps is not None:
durations = [1.0 / fps for image in sequence]
self.images_starts = [
1.0 * i / fps - np.finfo(np.float32).eps for i in range(len(sequence))
]
else:
self.images_starts = [0] + list(np.cumsum(durations))
self.durations = durations
self.duration = sum(durations)
self.end = self.duration
self.sequence = sequence
if fps is None:
self.fps = self.duration / len(sequence)
def find_image_index(t):
return max(
[i for i in range(len(self.sequence)) if self.images_starts[i] <= t]
)
if fromfiles:
self.last_index = None
self.last_image = None
def frame_function(t):
index = find_image_index(t)
if index != self.last_index:
self.last_image = imread(self.sequence[index])[:, :, :3]
self.last_index = index
return self.last_image
if with_mask and (imread(self.sequence[0]).shape[2] == 4):
self.mask = VideoClip(is_mask=True)
self.mask.last_index = None
self.mask.last_image = None
def mask_frame_function(t):
index = find_image_index(t)
if index != self.mask.last_index:
frame = imread(self.sequence[index])[:, :, 3]
self.mask.last_image = frame.astype(float) / 255
self.mask.last_index = index
return self.mask.last_image
self.mask.frame_function = mask_frame_function
self.mask.size = mask_frame_function(0).shape[:2][::-1]
else:
def frame_function(t):
index = find_image_index(t)
return self.sequence[index][:, :, :3]
if with_mask and (self.sequence[0].shape[2] == 4):
self.mask = VideoClip(is_mask=True)
def mask_frame_function(t):
index = find_image_index(t)
return 1.0 * self.sequence[index][:, :, 3] / 255
self.mask.frame_function = mask_frame_function
self.mask.size = mask_frame_function(0).shape[:2][::-1]
self.frame_function = frame_function
self.size = frame_function(0).shape[:2][::-1]