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vviz.py
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vviz.py
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#!/usr/bin/env python
from __future__ import print_function
import argparse
import os
from ffprobe_parser import *
from mp4dump_parser import *
from models import *
import plotly
import plotly.graph_objs as go
import plotly.io as pio
import pandas as pd
import scipy
import pytz
import statistics
def test_pandas(frames):
df = pd.DataFrame.from_records([f.to_dict() for f in frames], index='start_time')
print(df)
def sec2ts(sec):
return datetime.fromtimestamp(sec, tz=pytz.UTC)
def get_fragment_data_from_track(track, start_time=None, end_time=None):
data = []
fragments = track.fragments
# No fragments?
if len(fragments) == 0:
return data
if (start_time and end_time):
fragments = list(filter(lambda f: f.start_time < end_time and f.end_time > start_time, fragments))
frag_bar = go.Bar(
x=[f.start_time for f in fragments],
y=[f.size for f in fragments],
text=[str(f.duration.total_seconds()) + "s" for f in fragments],
width=[f.duration.total_seconds()*1000 for f in fragments],
offset=0,
name="Fragment",
marker=dict(
color="rgba(127,127,127,0.2)",
line=dict(
width=2,
color="#444"
)
),
yaxis='y2',
textposition='inside',
hoverinfo="text",
hovertext=[f.to_label() for f in fragments]
)
data.append(frag_bar)
return data
def get_frame_data_from_stream(stream):
bars = [
dict(type=IFrame, color='#FFBB00', label='I-frame'),
dict(type=IDRFrame, color='#FF0000', label='IDR frame'),
dict(type=PFrame, color='#6AFA00', label='P-frame'),
dict(type=BFrame, color='#1900FF', label='B-frame'),
]
data = []
# Bars for frames (per type)
for b in bars:
frames = stream.get_frames_for_type(b['type'], strict=True)
d = go.Bar(
x=[f.start_time for f in frames],
y=[f.size for f in frames],
text=["frame {}".format(f.position) for f in frames],
width=[f.duration.total_seconds()*1000 for f in frames],
offset=[0 for f in frames],
name=b['label'],
marker=dict(
color=b['color']
),
hoverinfo="x+y+text+name"
)
data.append(d)
return data
def get_bitrate_data_from_stream(stream, window):
# turn frames into a pandas DataFrame indexed on start time
df = pd.DataFrame.from_records([f.to_dict() for f in stream.frames], index='start_time')
data = []
# Bitrate
means_expanding = df['bitrate'] \
.expanding() \
.mean()
bitrate_expanding = go.Scatter(
x=means_expanding.index,
y=means_expanding.values,
name="bitrate <br>(cumul mean)",
yaxis='y3',
mode="lines",
line=dict(
width=2,
color="#7842AB"
),
hoverinfo="x+y",
# stackgroup='bitrates',
# legendgroup = "bitrates"
)
data.append(bitrate_expanding)
# TODO - doesn't seem that using center=False provides the correct results.
# Peaks not aligned with i-frames as I assume it should
means_rolling = df['bitrate'] \
.rolling(window=int(stream.frame_rate * window),
win_type='triang',
center=True,
min_periods=0
) \
.mean()
bitrate_rolling = go.Scatter(
x=means_rolling.index,
y=means_rolling.values,
name="bitrate <br>(sliding - {}s)".format(window),
yaxis='y3',
mode="lines",
line=dict(
width=1,
color="#9467BD"
),
hoverinfo="x+y",
fill="tonexty",
fillcolor="rgba(225,213,246,0.4)"
# stackgroup='bitrates'
# legendgroup="bitrates",
)
data.append(bitrate_rolling)
return data
def get_gop_data_from_stream(stream):
data = []
gops = stream.gops
bars = [
dict(closed=True, color='rgb(235, 188, 188)', label='Closed GOP'),
dict(closed=False, color='rgb(234, 220, 190)', label='Open GOP'),
]
for bar in bars:
# Bars for GOPs
goplist = list(filter(lambda g: g.closed == bar['closed'], gops))
gop_bar = go.Bar(
x=[gop.start_time for gop in goplist],
y=[gop.size for gop in goplist],
text=[gop.length for gop in goplist],
width=[gop.duration.total_seconds()*1000 for gop in goplist],
offset=0,
name=bar['label'],
marker=dict(
color=bar['color'],
line=dict(
width=1,
color="#111111"
)
),
yaxis='y2',
textposition='auto',
hoverinfo="text",
hovertext=[gop.to_label() for gop in stream.gops],
legendgroup='gops'
)
data.append(gop_bar)
return data
def plot_data(data, file, title, stream_label, track_label, resolution, formats):
filename = os.path.basename(file)
layout = go.Layout(
title="{}<br>{}".format(title, filename),
autosize=True,
# width=1500,
# height=800,
xaxis=dict(
title='',
tickmode='auto',
ticks='outside',
showticklabels=True,
dtick=1,
tickformat="%X.%2f",
tickfont=dict(
size=12,
color='rgb(107, 107, 107)'
),
range=[
stream.frames[0].start_time,
stream.frames[-1].end_time
]
),
yaxis=dict(
domain=[0.30, 1],
title='frame size (b)',
titlefont=dict(
size=14,
color='rgb(107, 107, 107)'
),
showticklabels=True,
ticks='outside',
tickfont=dict(
size=10,
),
fixedrange=True,
hoverformat='.3s'
),
yaxis2=dict(
domain=[0, 0.25],
title='size (b)',
titlefont=dict(
size=14
),
side='left',
showticklabels=True,
ticks='outside',
tickfont=dict(
size=10,
),
showgrid=False,
anchor='x',
spikesnap="data",
spikemode="toaxis+across+marker",
spikethickness=1,
spikedash='dot',
fixedrange=True
),
yaxis3=dict(
domain=[0.30, 1],
title='bitrate (bps)',
titlefont=dict(
color="#CDA8F0",
size=14
),
side='right',
showticklabels=True,
ticks='outside',
tickfont=dict(
size=10,
color="#CDA8F0"
),
showgrid=False,
anchor='x',
overlaying='y',
showspikes=True,
spikesnap="data",
spikemode="toaxis+across+marker",
spikethickness=1,
spikedash='dot',
fixedrange=False,
hoverformat='.3s'
),
legend=dict(
x=1.06,
traceorder="normal"
),
annotations=[
dict(
x=1.03,
y=0.3,
xref='paper',
yref='paper',
xanchor='left',
yanchor='bottom',
xshift=0,
yshift=0,
showarrow=False,
text=stream_label,
borderpad=1,
bgcolor="#F5FFFA",
bordercolor="#d2cdcd",
borderwidth=1,
align="left"
),
dict(
x=1.03,
y=0.20,
xref='paper',
yref='paper',
xanchor='left',
yanchor='top',
xshift=0,
yshift=0,
showarrow=False,
text=track_label,
borderpad=1,
bgcolor="#F0FFFF",
bordercolor="#d2cdcd",
borderwidth=1,
align="left"
),
dict(
x=1,
xshift=200,
y=0,
yshift=-50,
xref='paper',
yref='paper',
xanchor='right',
yanchor='bottom',
showarrow=False,
text="generated " + datetime.now().strftime("%d-%b-%y %X") + " - github.com/wabiloo/vviz_py",
align="right"
)
],
)
if 'interactive' in formats:
print("Generating interactive HTML output to {}.html".format(args.path_to_file))
plotly.offline.plot({
"data": data,
"layout": layout
},
auto_open=True,
filename="{}.html".format(file),
image_width=1000, image_height=600, image='svg'
)
for format in formats:
if format != 'interactive':
print ("Generating {} output to {}.{}".format(format, args.path_to_file, format) )
pio.write_image({
"data": data,
"layout": layout
},
file=file + '.' + format,
width=resolution[0],
height=resolution[1]
)
if __name__ == "__main__":
print(os.environ['PATH'])
parser = argparse.ArgumentParser(description='Chart generator (interactive and static) for video file analysis (frames, streams, fragments, gops, etc.)')
parser.add_argument('path_to_file', help='video file to parse')
parser.add_argument('--ffprobe-exec', dest='ffprobe_exec',
help='ffprobe executable. (default: %(default)s)',
default='ffprobe')
parser.add_argument('--mp4dump-exec', dest='mp4dump_exec',
help='mp4dump executable. (default: %(default)s)',
default='mp4dump')
parser.add_argument('--intervals', dest='intervals',
help='interval to read from video file (see ffprobe -read_intervals parameter)')
parser.add_argument('--streams', dest='streams',
help='streams to read from video file (see ffprobe -select_streams parameter)',
default='v:0')
parser.add_argument('-t', '--title', dest='title',
help='title for the chart (in addition to filename)',
default='Frame, GOP and Fragment Analysis')
parser.add_argument('-b', '--window', dest='window', type=float,
help='size of the window (in seconds) used to calculate average bitrates',
default=1.0)
parser.add_argument('-f', '--formats', dest='formats', nargs="*", choices=['interactive', 'svg', 'pdf', 'png', 'webp'],
help='1 or multiple output formats',
default=['interactive'])
parser.add_argument('-r', '--resolution', dest='resolution', nargs=2, type=int,
help='resolution (width and height) for output images',
default=[1200, 600])
args = parser.parse_args()
filename = os.path.basename(args.path_to_file)
interval = args.intervals if args.intervals else None
ffprobe = FFProbeCommand(executable=args.ffprobe_exec,
filename=args.path_to_file,
intervals=interval,
streams=args.streams)
fresponse = ffprobe.call()
stream = Stream(origin=fresponse, stream_index=0)
mp4dump = MP4DumpCommand(executable=args.mp4dump_exec,
filename=args.path_to_file)
mresponse = mp4dump.call()
track = MP4Track(parser=mresponse)
# test_pandas(stream.frames)
data = []
data += get_frame_data_from_stream(stream)
data += get_bitrate_data_from_stream(stream, args.window)
# filtering necessary as mp4dump does not offer command line parameters for it
if (interval):
data += get_fragment_data_from_track(track,
start_time=stream.frames[0].start_time,
end_time=stream.frames[-1].end_time)
else:
data += get_fragment_data_from_track(track)
data += get_gop_data_from_stream(stream)
plot_data(data,
args.path_to_file,
title=args.title,
stream_label=stream.to_label(),
track_label=track.to_label(),
resolution=args.resolution,
formats=args.formats)