Optimized library for large-scale extraction of frames and audio from video.
pip install video2numpy
Or build from source:
python setup.py install
NAME
video2numpy - Read frames from videos and save as numpy arrays
SYNOPSIS
video2numpy SRC <flags>
DESCRIPTION
Input:
src:
str: path to mp4 file
str: youtube link
str: path to txt file with multiple mp4's or youtube links
list: list with multiple mp4's or youtube links
dest:
str: directory where to save frames to
None: dest = src + .npy
take_every_nth:
int: only take every nth frame
resize_size:
int: new pixel height and width of resized frame
workers:
int: number of workers used to read videos
memory_size:
int: number of GB of shared memory used for reading, use larger shared memory for more videos
POSITIONAL ARGUMENTS
SRC
FLAGS
--dest=DEST
Default: ''
--take_every_nth=TAKE_EVERY_NTH
Default: 1
--resize_size=RESIZE_SIZE
Default: 224
--workers=WORKERS
Default: 1
--memory_size=MEMORY_SIZE
Default: 4
NOTES
You can also use flags syntax for POSITIONAL ARGUMENTS
This module exposes a single function video2numpy which takes the same arguments as the command line tool:
import glob
from video2numpy import video2numpy
VIDS = glob.glob("some/path/my_videos/*.mp4")
FRAME_DIR = "some/path/my_frames"
take_every_5 = 5
video2numpy(VIDS, FRAME_DIR, take_every_5)You can also directly use the reader and iterate over videos yourself:
import glob
from video2numpy.frame_reader import FrameReader
VIDS = glob.glob("some/path/my_videos/*.mp4")
take_every_5 = 5
resize_size = 300
batch_size = 64 # output shape will be (n, batch_size, height, width, 3)
reader = FrameReader(VIDS, take_every_5, resize_size, batch_size)
reader.start_reading()
for vid_frames, info_dict in reader:
# info_dict["dst_name"] - name for saving numpy array
# info_dict["pad_by"] - how many pad frames were added to final block so n_frames % batch_size == 0
# do something with vid_frames of shape (n_blocks, 64, 300, 300, 3)
...Either locally, or in gitpod (do export PIP_USER=false there)
Setup a virtualenv:
python3 -m venv .env
source .env/bin/activate
pip install -e .
to run tests:
pip install -r requirements-test.txt
then
make lint
make test
You can use make black to reformat the code
python -m pytest -x -s -v tests -k "dummy" to run a specific test