A Key Frame
is a location on a video timeline which marks the beginning or end of a smooth transition throughout the fotograms, Key Frame Detector
try to look for the most representative and significant frames that can describe the movement or main events in a video using peakutils peak detection functions.
Requirements
- python3
- numpy
- opencv
- peakutils
- matplotlib
- PIL
pip install video-keyframe-detector
After installing the package (see Installation section), you can run the keyframe detector from the terminal:
# After installation, run the detector with your video file:
video-keyframe-detector -s "path/to/your/video.mp4" -d output/ -t 0.3
# Or if running from source:
# git clone https://github.com/joelibaceta/video-keyframe-detector
# cd video-keyframe-detector
# pip install -r requirements.txt
# python3 cli.py -s "videos/acrobacia.mp4" -d output/ -t 0.3
You can also use the detector directly in your Python code:
from KeyFrameDetector.key_frame_detector import keyframeDetection
source_video = "videos/acrobacia.mp4"
output_dir = "output"
threshold = 0.3
keyframeDetection(
source=source_video,
dest=output_dir,
Thres=threshold,
max_keyframes=5,
plotMetrics=True,
verbose=True
)