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# RTC frame size variation analyzer
# Usage:
# 1. Config with "-DCONFIG_OUTPUT_FRAME_SIZE=1".
# 2. Build aomenc. Encode a file, and generate output file: frame_sizes.csv
# 3. Run: python ./frame_size.py frame_sizes.csv target-bitrate fps
# Where target-bitrate: Bitrate (kbps), and fps is frame per second.
# Example: python ../aom/tools/frame_size_variation_analyzer.py frame_sizes.csv
# 1000 30
import numpy as np
import csv
import sys
import matplotlib.pyplot as plt
# return the moving average
def moving_average(x, w):
return np.convolve(x, np.ones(w), 'valid') / w
def frame_size_analysis(filename, target_br, fps):
tbr = target_br * 1000 / fps
with open(filename, 'r') as infile:
raw_data = list(csv.reader(infile, delimiter=','))
data = np.array(raw_data).astype(float)
fsize = data[:, 0].astype(float) # frame size
qindex = data[:, 1].astype(float) # qindex
# Frame bit rate mismatch
mismatch = np.absolute(fsize - np.full(fsize.size, tbr))
# Count how many frames are more than 2.5x of frame target bit rate.
tbr_thr = tbr * 2.5
cnt = 0
idx = np.arange(fsize.size)
for i in idx:
if fsize[i] > tbr_thr:
cnt = cnt + 1
# Use the 15-frame moving window
win = 15
avg_fsize = moving_average(fsize, win)
win_mismatch = np.absolute(avg_fsize - np.full(avg_fsize.size, tbr))
print('[Target frame rate (bit)]:', "%.2f"%tbr)
print('[Average frame rate (bit)]:', "%.2f"%np.average(fsize))
print('[Frame rate standard deviation]:', "%.2f"%np.std(fsize))
print('[Max/min frame rate (bit)]:', "%.2f"%np.max(fsize), '/', "%.2f"%np.min(fsize))
print('[Average frame rate mismatch (bit)]:', "%.2f"%np.average(mismatch))
print('[Number of frames (frame rate > 2.5x of target frame rate)]:', cnt)
print(' Moving window size:', win)
print('[Moving average frame rate mismatch (bit)]:', "%.2f"%np.average(win_mismatch))
print('------------------------------')
figure, axis = plt.subplots(2)
x = np.arange(fsize.size)
axis[0].plot(x, fsize, color='blue')
axis[0].set_title("frame sizes")
axis[1].plot(x, qindex, color='blue')
axis[1].set_title("frame qindex")
plt.tight_layout()
# Save the plot
plotname = filename + '.png'
plt.savefig(plotname)
plt.show()
if __name__ == '__main__':
if (len(sys.argv) < 4):
print(sys.argv[0], 'input_file, target_bitrate, fps')
sys.exit()
target_br = int(sys.argv[2])
fps = int(sys.argv[3])
frame_size_analysis(sys.argv[1], target_br, fps)
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