tempslice
Produces an image containing a column of pixels for every input frame. The number and location of the pixels is chosen by the user by defining a start and end point over the input images. All images must be the same resolution.
Use:
python3 tempslice.py -s 560 584 -e 620 584 -i /home/user/image_directory/*.png -o ./exampleHelp output:
usage: tempslice.py [-h] -s START START -e END END -i INPUT [INPUT ...] [-o OUTPUT]
Produces a PIL image containing a column of pixels for every input image. The number and location of the pixels is chosen by the user by defining a start and
end point over the input images. All images must be the same resolution.
required arguments:
-s START START, --start START START
Starting point coordinates of the line as x y
-e END END, --end END END
Ending point coordinates of the line as x,y
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
List of input files
optional arguments:
-o OUTPUT, --output OUTPUT
Path for 2 output files containing the slice and the first frame with the slice location. E.g. /home/user/Documents/output_file_name
which will result in /home/user/Documents/output_file_name_loc.png & /home/user/Documents/output_file_name_slice.png
slice2csv
Utility to convert image slices into a csv by thresholding 2 differently colored regions of the slice
Use:
python3 slice2csv.py -u 203 5 -l 244 32 -t 16 -i ./../demo_vid_IQS/5Hz_50mV_1_amped_slice.png -o ./../demo_vid_IQS/ -v TrueHelp output:
usage: slice2csv.py [-h] -u UPPER UPPER -l LOWER LOWER -t THRESHOLD -i INPUT [INPUT ...] -o OUTPUT [-v VERBOSE] [-vs VERBOSE_SAVE]
Converts a slice into a csv file by thresholding upper and lower color to find a waveform in it's boundary.
required arguments:
-u UPPER UPPER, --upper UPPER UPPER
Upper pixel example coordinates as x y
-l LOWER LOWER, --lower LOWER LOWER
Lower pixel example coordinates as x y
-t THRESHOLD, --threshold THRESHOLD
Maximum colour difference
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
List of input files
-o OUTPUT, --output OUTPUT
Path for csv output files
optional arguments:
-v VERBOSE, --verbose VERBOSE
Shows the waveform detected over the image. Red=upper point, Green=lower point, Blue=average
-vs VERBOSE_SAVE, --verbose_save VERBOSE_SAVE
Saves the waveform detected over the image.(verbose flag must be True)
csv-fft
Utility to plot an unrefined fft from slice2csv files
Help output:
usage: csv-fft.py [-h] -f SAMPLE_RATE -i INPUT [INPUT ...] [-o OUTPUT] [-od OUTPUT_DATA] [--dpi DPI] [-c FREQ_CAP FREQ_CAP] [-m {abs,imag}] [-s {log,mag}]
[--data_col {avg,lub,ulb}] [--smooth SMOOTH] [-w {none,hamming,bartlett,blackman,hanning}]
Plots the fft(s) of the input slices csv
required arguments:
-f SAMPLE_RATE, --sample_rate SAMPLE_RATE
Sample rate in Hz (or fps)
-i INPUT [INPUT ...], --input INPUT [INPUT ...]
List of input files
optional arguments:
-o OUTPUT, --output OUTPUT
Path for the output graph
-od OUTPUT_DATA, --output_data OUTPUT_DATA
Path for csv output files
--dpi DPI Output graph dpi
-c FREQ_CAP FREQ_CAP, --freq_cap FREQ_CAP FREQ_CAP
Frequency graph cutoff as: start end
-m {abs,imag}, --mode {abs,imag}
Path for the output graph
-s {log,mag}, --scale {log,mag}
Enable logarithmic scale on the y axis
--data_col {avg,lub,ulb}
Data column to be used for fft, by default averages both columns
--smooth SMOOTH Smoothing factor [0-1]. Smoothens data using a cubic spline approximation
-w {none,hamming,bartlett,blackman,hanning}, --window {none,hamming,bartlett,blackman,hanning}
Apply window before FFT
threshold-slice
Thresholds a slice to black and white, to improve wave detection
Help output:
usage: threshold-slice.py [-h] -t THRESHOLD -i INPUT -o OUTPUT [-v VERBOSE]
Thresholds a slice to black and white, to improve wave detection
required arguments:
-t THRESHOLD, --threshold THRESHOLD
Grayscale limit for thresholding
-i INPUT, --input INPUT
Input file
-o OUTPUT, --output OUTPUT
Path for output file
optional arguments:
-v VERBOSE, --verbose VERBOSE
Shows both the original and the thresholded images
csv-specgram
Plots the spectrogram of the input slice csv
Help output:
usage: csv-specgram.py [-h] -f SAMPLE_RATE -i INPUT [-o OUTPUT] [--dpi DPI] [-c FREQ_CAP FREQ_CAP] [-s {log,mag}] [--data_col {avg,lub,ulb}] [-w {none,hamming,bartlett,blackman,hanning}]
Plots the spectrogram of the input slice csv
required arguments:
-f SAMPLE_RATE, --sample_rate SAMPLE_RATE
Sample rate in Hz (or fps)
-i INPUT, --input INPUT
List of input files
optional arguments:
-o OUTPUT, --output OUTPUT
Path for the output graph
--dpi DPI Output graph dpi
-c FREQ_CAP FREQ_CAP, --freq_cap FREQ_CAP FREQ_CAP
Frequency graph cutoff as: start end
-s {log,mag}, --scale {log,mag}
Enable logarithmic scale on the y axis
--data_col {avg,lub,ulb}
Data column to be used for fft, by default averages both columns
-w {none,hamming,bartlett,blackman,hanning}, --window {none,hamming,bartlett,blackman,hanning}
Apply window before FFT
csv-smooth
Smoothes data from a csv using a cubic spline approximation
usage: csv-smooth.py [-h] -i INPUT [-o OUTPUT] [--data_col {avg,lub,ulb}] [-s SMOOTH] [-p PLOT]
Smoothens data from a csv using a cubic spline approximation
required arguments:
-i INPUT, --input INPUT
List of input files
optional arguments:
-o OUTPUT, --output OUTPUT
Path for the output file
--data_col {avg,lub,ulb}
Data column to be used for fft, by default averages both columns
-s SMOOTH, --smooth SMOOTH
Smoothing factor [0-1]. Defaults to 0.85.
-p PLOT, --plot PLOT Plot the resulting function