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Creating test video - 2020

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lavfi - Libavfilter input virtual device

"This input device reads data from the open output pads of a libavfilter filtergraph. For each filtergraph open output, the input device will create a corresponding stream which is mapped to the generated output. Currently only video data is supported. The filtergraph is specified through the option graph" - from ffmpeg-devices.





testsrc

The testsrc filter generates a test video pattern showing a color pattern, a scrolling gradient, and a timestamp. This is useful for testing purposes.

This example will create a 10 second output, 30 fps (300 frames total), with a frame size of 640x360 (testsrc.mpg):

ffmpeg -f lavfi -i testsrc=duration=10:size=1280x720:rate=30 testsrc.mpg
Your browser does not support the video tag.




The following command will generate a video with a duration of 5.3 seconds, with size 176x144 and a frame rate of 10 frames per second.

ffmpeg -f lavfi -i testsrc=duration=5.3:size=qcif:rate=10 testsrc2.mp4
Your browser does not support the video tag.



smptebars

The smptebars source generates a color bars pattern, based on the SMPTE Engineering Guideline EG 1-1990.

The smptehdbars source generates a color bars pattern, based on the SMPTE RP 219-2002.

This example will create a 10 second output, 30 fps (300 frames total), with a frame size of 640x360:

ffmpeg -f lavfi -i smptebars=duration=10:size=640x360:rate=30 smptebars.mp4

Your browser does not support the video tag.




color source

The following graph description will generate a red source with an opacity of 0.2, with size "qcif" and a frame rate of 10 frames per second with the duration of 5 seconds.

ffmpeg -f lavfi -i color=c=red@0.2:duration=5:s=qcif:r=10 colorsrc.mp4

Your browser does not support the video tag.



rgbtestsrc

The rgbtestsrc source generates an RGB test pattern useful for detecting RGB vs BGR issues. We should see a red, green and blue stripe from top to bottom.

ffmpeg -f lavfi -i rgbtestsrc -pix_fmt yuv420p -t 5 rgbtestsrc.mp4

Your browser does not support the video tag.









Ph.D. / Golden Gate Ave, San Francisco / Seoul National Univ / Carnegie Mellon / UC Berkeley / DevOps / Deep Learning / Visualization

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Thank you.

- K Hong







FFmpeg image & video processing



Image/video scaling

Image/video cropping

Cropdetect and ffplay

Speeding-up & slowing-down video

Basic slide show from images

Advanced slide show from images

Thumbnails -Selecting specific frames : I-frame extraction etc.

Creating a mosaic/tile of screenshots from a movie

Seeking and cutting sections of a video & audio

Concatenating two video files or two audio files

Transitions : fade-in & fade-out for 1 slide

Transitions : python script for fade-in & fade-out with two slides

Concatenate slides

Creating test videos

Screen Recording on Ubuntu A

Active window capture with Python on Ubuntu B




Sponsor Open Source development activities and free contents for everyone.

Thank you.

- K Hong







OpenCV 3 -

image & video processing



Installing on Ubuntu 13

Mat(rix) object (Image Container)

Creating Mat objects

The core : Image - load, convert, and save

Smoothing Filters A - Average, Gaussian

Smoothing Filters B - Median, Bilateral






OpenCV 3 image and video processing with Python



OpenCV 3 with Python

Image - OpenCV BGR : Matplotlib RGB

Basic image operations - pixel access

iPython - Signal Processing with NumPy

Signal Processing with NumPy I - FFT and DFT for sine, square waves, unitpulse, and random signal

Signal Processing with NumPy II - Image Fourier Transform : FFT & DFT

Inverse Fourier Transform of an Image with low pass filter: cv2.idft()

Image Histogram

Video Capture and Switching colorspaces - RGB / HSV

Adaptive Thresholding - Otsu's clustering-based image thresholding

Edge Detection - Sobel and Laplacian Kernels

Canny Edge Detection

Hough Transform - Circles

Watershed Algorithm : Marker-based Segmentation I

Watershed Algorithm : Marker-based Segmentation II

Image noise reduction : Non-local Means denoising algorithm

Image object detection : Face detection using Haar Cascade Classifiers

Image segmentation - Foreground extraction Grabcut algorithm based on graph cuts

Image Reconstruction - Inpainting (Interpolation) - Fast Marching Methods

Video : Mean shift object tracking

Machine Learning : Clustering - K-Means clustering I

Machine Learning : Clustering - K-Means clustering II

Machine Learning : Classification - k-nearest neighbors (k-NN) algorithm



Matlab Image and Video Processing



Vectors and Matrices

m-Files (Scripts)

For loop

Indexing and masking

Vectors and arrays with audio files

Manipulating Audio I

Manipulating Audio II

Introduction to FFT & DFT

Discrete Fourier Transform (DFT)



Digital Image Processing 2 - RGB image & indexed image

Digital Image Processing 3 - Grayscale image I

Digital Image Processing 4 - Grayscale image II (image data type and bit-plane)

Digital Image Processing 5 - Histogram equalization

Digital Image Processing 6 - Image Filter (Low pass filters)

Video Processing 1 - Object detection (tagging cars) by thresholding color

Video Processing 2 - Face Detection and CAMShift Tracking












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