A package that provides helpful utilities to interact with videos and images through OpenCV.
Project description
imgvid_utils
This repository is intended to provide useful functions for concatenating, stacking, and splitting images and video files.
The CLI provides access to these functions: Stacking images vertically:
python -m imgvid_utils --vstack image1.jpg image2.jpg --name output.png
Stacking images horizontally:
python -m imgvid_utils --hstack image1.jpg image2.jpg --name output.png
Stacking images in an arbitrary fashion:
python -m imgvid_utils --files_in image1.jpg .. image25.jpg --rows 5 --cols 5 --name output.png
Stacking images in an arbitrary fashion from many directories:
python -m imgvid_utils --dirs_in dir1 ... dir25 --rows 5 --cols 5 --name output.png --to_imgs
Stacking videos in an arbitrary fashion from many source files:
python -m imgvid_utils --files_in video1.mp4 ... video25.mp4 --rows 5 --cols 5 --name output.mp4 --to_vid
Stacking videos in an arbitrary fashion from many directories:
python -m imgvid_utils --dirs_in dir1 ... dir25 rows 5 --cols 5 --name output.mp4 --to_vid
Splitting videos into component frames:
python -m imgvid_utils --files_in video1 --name output.png --to_imgs
Finding images with matching file names and concatenating them:
python -m imgvid_utils --dirs_in dir1 dir2 --read_matching_file_names
Examples
Defining a stacking
from imgvid_utils.image import Stacking
stacking = Stacking(2, 2, "rd")
This stacking has 2 columns, 2 rows, and will stack images to the right and downwards.
Stacking images in an arbitrary fashion:
python -m imgvid_utils --files_in image1.jpg .. image25.jpg --rows 5 --cols 5 --name output.png
Using the API
imgvid_utils provides a flexible API based on frame sources and sinks.
Defining frame sources
from imgvid_utils import image as ims
from imgvid_utils import video as vs
# Groups the images by order of appearance in the provided lists
ims.FileIterator(
[["file1.png", "file2.jpg", "file3.png"], ["file1.jpg", "file2.png", ...], ...],
stacking=ims.Stacking(1, 2, "rd")
)
# Groups images by order of appearance in the provided directories
ims.DirectoryIterator(
["./path_to_first_directory", "./path_to_second_directory"],
stacking=ims.Stacking(1, 2, "rd")
)
# A variant of DirectoryIterator which groups images with matching file names
# Output images are returned in lexographical order
ims.DirectoryIteratorMatchNames(
["./path_to_first_directory", "./path_to_second_directory"],
stacking=ims.Stacking(1, 2, "rd")
)
# Groups the nth frame in each video
vs.VideoIterator(
["video1.mp4", "video2.mp4"],
stacking=ims.Stacking(1, 2, "rd"),
)
Resizing all input frames
source.resize_in((640, 480))
Resizing input frames on an individual basis
source.resize(ims.Resize.FIRST)
# Choices are
# Resize.FIRST: Chooses the first set of dimensions
# Resize.UP: Chooses the dimensions with the largest area
# Resize.DOWN: Chooses the dimensions with the smallest area
Controlling which frames are selected
# Skips the first 10 frames of input, and output only 10 frames
source.skip(10).take(10)
Chaining iterators:
# Note: Resize transformations should only be applied once to avoid resizing artifacts
source = source1.chain(source2).resize(resize)
Creating output
Writing files to a target directory
source.write_images("output_dir", "prefix", "extension", self.choose_padding())
Writing files to a video
### Requires source.resize_in() to be called first
source.write_video("path/to/video.mp4", video_format="mp4v", fps=24.0)
Processing images manually
for image_data in source:
file_name = image_data.file_name
ext = image_data.ext
image = image_data.images[0]
do_something(file_name, ext, image)
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