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Exemple de boutons d’action pour une collection collaborative
27 février 2013, par
Mis à jour : Mars 2013
Langue : français
Type : Image
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Exemple de boutons d’action pour une collection personnelle
27 février 2013, par
Mis à jour : Février 2013
Langue : English
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Autres articles (39)
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Sur d’autres sites (6422)
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Trying to get the current FPS and Frametime value into Matplotlib title
16 juin 2022, par TiSoBrI try to turn an exported CSV with benchmark logs into an animated graph. Works so far, but I can't get the Titles on top of both plots with their current FPS and frametime in ms values animated.


Thats the output I'm getting. Looks like he simply stores all values in there instead of updating them ?


Screengrab of cli output
Screengrab of the final output (inverted)


from __future__ import division
import sys, getopt
import time
import matplotlib
import numpy as np
import subprocess
import math
import re
import argparse
import os
import glob

import matplotlib.animation as animation
import matplotlib.pyplot as plt


def check_pos(arg):
 ivalue = int(arg)
 if ivalue <= 0:
 raise argparse.ArgumentTypeError("%s Not a valid positive integer value" % arg)
 return True
 
def moving_average(x, w):
 return np.convolve(x, np.ones(w), 'valid') / w
 

parser = argparse.ArgumentParser(
 description = "Example Usage python frame_scan.py -i mangohud -c '#fff' -o mymov",
 formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("-i", "--input", help = "Input data set from mangohud", required = True, nargs='+', type=argparse.FileType('r'), default=sys.stdin)
parser.add_argument("-o", "--output", help = "Output file name", required = True, type=str, default = "")
parser.add_argument("-r", "--framerate", help = "Set the desired framerate", required = False, type=float, default = 60)
parser.add_argument("-c", "--colors", help = "Colors for the line graphs; must be in quotes", required = True, type=str, nargs='+', default = 60)
parser.add_argument("--fpslength", help = "Configures how long the data will be shown on the FPS graph", required = False, type=float, default = 5)
parser.add_argument("--fpsthickness", help = "Changes the line width for the FPS graph", required = False, type=float, default = 3)
parser.add_argument("--frametimelength", help = "Configures how long the data will be shown on the frametime graph", required = False, type=float, default = 2.5)
parser.add_argument("--frametimethickness", help = "Changes the line width for the frametime graph", required = False, type=float, default = 1.5)
parser.add_argument("--graphcolor", help = "Changes all of the line colors on the graph; expects hex value", required = False, default = '#FFF')
parser.add_argument("--graphthicknes", help = "Changes the line width of the graph", required = False, type=float, default = 1)
parser.add_argument("-ts","--textsize", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 23)
parser.add_argument("-fsM","--fpsmax", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 180)
parser.add_argument("-fsm","--fpsmin", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 0)
parser.add_argument("-fss","--fpsstep", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 30)
parser.add_argument("-ftM","--frametimemax", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 50)
parser.add_argument("-ftm","--frametimemin", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 0)
parser.add_argument("-fts","--frametimestep", help = "Changes the the size of numbers marking the ticks", required = False, type=float, default = 10)

arg = parser.parse_args()
status = False


if arg.input:
 status = True
if arg.output:
 status = True
if arg.framerate:
 status = check_pos(arg.framerate)
if arg.fpslength:
 status = check_pos(arg.fpslength)
if arg.fpsthickness:
 status = check_pos(arg.fpsthickness)
if arg.frametimelength:
 status = check_pos(arg.frametimelength)
if arg.frametimethickness:
 status = check_pos(arg.frametimethickness)
if arg.colors:
 if len(arg.output) != len(arg.colors):
 for i in arg.colors:
 if re.match(r"^#([A-Fa-f0-9]{6}|[A-Fa-f0-9]{3})$", i):
 status = True
 else:
 print('{} : Isn\'t a valid hex value!'.format(i))
 status = False
 else:
 print('You must have the same amount of colors as files in input!')
 status = False
if arg.graphcolor:
 if re.match(r"^#([A-Fa-f0-9]{6}|[A-Fa-f0-9]{3})$", arg.graphcolor):
 status = True
 else:
 print('{} : Isn\'t a vaild hex value!'.format(arg.graphcolor))
 status = False
if arg.graphthicknes:
 status = check_pos(arg.graphthicknes)
if arg.textsize:
 status = check_pos(arg.textsize)
if not status:
 print("For a list of arguments try -h or --help") 
 exit()


# Empty output folder
files = glob.glob('/output/*')
for f in files:
 os.remove(f)


# We need to know the longest recording out of all inputs so we know when to stop the video
longest_data = 0

# Format the raw data into a list of tuples (fps, frame time in ms, time from start in micro seconds)
# The first three lines of our data are setup so we ignore them
data_formated = []
for li, i in enumerate(arg.input):
 t = 0
 sublist = []
 for line in i.readlines()[3:]:
 x = line[:-1].split(',')
 fps = float(x[0])
 frametime = int(x[1])/1000 # convert from microseconds to milliseconds
 elapsed = int(x[11])/1000 # convert from nanosecond to microseconds
 data = (fps, frametime, elapsed)
 sublist.append(data)
 # Compare last entry of each list with the 
 if sublist[-1][2] >= longest_data:
 longest_data = sublist[-1][2]
 data_formated.append(sublist)


max_blocksize = max(arg.fpslength, arg.frametimelength) * arg.framerate
blockSize = arg.framerate * arg.fpslength


# Get step time in microseconds
step = (1/arg.framerate) * 1000000 # 1000000 is one second in microseconds
frame_size_fps = (arg.fpslength * arg.framerate) * step
frame_size_frametime = (arg.frametimelength * arg.framerate) * step


# Total frames will have to be updated for more then one source
total_frames = int(int(longest_data) / step)


if True: # Gonna be honest, this only exists so I can collapse this block of code

 # Sets up our figures to be next to each other (horizontally) and with a ratio 3:1 to each other
 fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})

 # Size of whole output 1920x360 1080/3=360
 fig.set_size_inches(19.20, 3.6)

 # Make the background transparent
 fig.patch.set_alpha(0)


 # Loop through all active axes; saves a lot of lines in ax1.do_thing(x) ax2.do_thing(x)
 for axes in fig.axes:

 # Set all splines to the same color and width
 for loc, spine in axes.spines.items():
 axes.spines[loc].set_color(arg.graphcolor)
 axes.spines[loc].set_linewidth(arg.graphthicknes)

 # Make sure we don't render any data points as this will be our background
 axes.set_xlim(-(max_blocksize * step), 0)
 

 # Make both plots transparent as well as the background
 axes.patch.set_alpha(.5)
 axes.patch.set_color('#020202')

 # Change the Y axis info to be on the right side
 axes.yaxis.set_label_position("right")
 axes.yaxis.tick_right()

 # Add the white lines across the graphs; the location of the lines are based off set_{}ticks
 axes.grid(alpha=.8, b=True, which='both', axis='y', color=arg.graphcolor, linewidth=arg.graphthicknes)

 # Remove X axis info
 axes.set_xticks([])

 # Add a another Y axis so ticks are on both sides
 tmp_ax1 = ax1.secondary_yaxis("left")
 tmp_ax2 = ax2.secondary_yaxis("left")

 # Set both to the same values
 ax1.set_yticks(np.arange(arg.fpsmin, arg.fpsmax + 1, step=arg.fpsstep))
 ax2.set_yticks(np.arange(arg.frametimemin, arg.frametimemax + 1, step=arg.frametimestep))
 tmp_ax1.set_yticks(np.arange(arg.fpsmin , arg.fpsmax + 1, step=arg.fpsstep))
 tmp_ax2.set_yticks(np.arange(arg.frametimemin, arg.frametimemax + 1, step=arg.frametimestep))

 # Change the "ticks" to be white and correct size also change font size
 ax1.tick_params(axis='y', color=arg.graphcolor ,width=arg.graphthicknes, length=16, labelsize=arg.textsize, labelcolor=arg.graphcolor)
 ax2.tick_params(axis='y', color=arg.graphcolor ,width=arg.graphthicknes, length=16, labelsize=arg.textsize, labelcolor=arg.graphcolor)
 tmp_ax1.tick_params(axis='y', color=arg.graphcolor ,width=arg.graphthicknes, length=8, labelsize=0) # Label size of 0 disables the fps/frame numbers
 tmp_ax2.tick_params(axis='y', color=arg.graphcolor ,width=arg.graphthicknes, length=8, labelsize=0)


 # Limits Y scale
 ax1.set_ylim(arg.fpsmin,arg.fpsmax + 1)
 ax2.set_ylim(arg.frametimemin,arg.frametimemax + 1)

 # Add an empty plot
 line = ax1.plot([], lw=arg.fpsthickness)
 line2 = ax2.plot([], lw=arg.frametimethickness)

 # Sets all the data for our benchmark
 for benchmarks, color in zip(data_formated, arg.colors):
 y = moving_average([x[0] for x in benchmarks], 25)
 y2 = [x[1] for x in benchmarks]
 x = [x[2] for x in benchmarks]
 line += ax1.plot(x[12:-12],y, c=color, lw=arg.fpsthickness)
 line2 += ax2.step(x,y2, c=color, lw=arg.fpsthickness)
 
 # Add titles with values
 ax1.set_title("Avg. frames per second: {}".format(y2), color=arg.graphcolor, fontsize=20, fontweight='bold', loc='left')
 ax2.set_title("Frametime in ms: {}".format(y2), color=arg.graphcolor, fontsize=20, fontweight='bold', loc='left') 

 # Removes unwanted white space; also controls the space between the two graphs
 plt.tight_layout(pad=0, h_pad=0, w_pad=2.5)
 
 fig.canvas.draw()

 # Cache the background
 axbackground = fig.canvas.copy_from_bbox(ax1.bbox)
 ax2background = fig.canvas.copy_from_bbox(ax2.bbox)


# Create a ffmpeg instance as a subprocess we will pipe the finished frame into ffmpeg
# encoded in Apple QuickTime (qtrle) for small(ish) file size and alpha support
# There are free and opensource types that will also do this but with much larger sizes
canvas_width, canvas_height = fig.canvas.get_width_height()
outf = '{}.mov'.format(arg.output)
cmdstring = ('ffmpeg',
 '-stats', '-hide_banner', '-loglevel', 'error', # Makes ffmpeg less annoying / to much console output
 '-y', '-r', '60', # set the fps of the video
 '-s', '%dx%d' % (canvas_width, canvas_height), # size of image string
 '-pix_fmt', 'argb', # format cant be changed since this is what `fig.canvas.tostring_argb()` outputs
 '-f', 'rawvideo', '-i', '-', # tell ffmpeg to expect raw video from the pipe
 '-vcodec', 'qtrle', outf) # output encoding must support alpha channel
pipe = subprocess.Popen(cmdstring, stdin=subprocess.PIPE)

def render_frame(frame : int):

 # Set the bounds of the graph for each frame to render the correct data
 start = (frame * step) - frame_size_fps
 end = start + frame_size_fps
 ax1.set_xlim(start,end)
 
 
 start = (frame * step) - frame_size_frametime
 end = start + frame_size_frametime
 ax2.set_xlim(start,end)
 

 # Restore background
 fig.canvas.restore_region(axbackground)
 fig.canvas.restore_region(ax2background)

 # Redraw just the points will only draw points with in `axes.set_xlim`
 for i in line:
 ax1.draw_artist(i)
 
 for i in line2:
 ax2.draw_artist(i)

 # Fill in the axes rectangle
 fig.canvas.blit(ax1.bbox)
 fig.canvas.blit(ax2.bbox)
 
 fig.canvas.flush_events()

 # Converts the finished frame to ARGB
 string = fig.canvas.tostring_argb()
 return string




#import multiprocessing
#p = multiprocessing.Pool()
#for i, _ in enumerate(p.imap(render_frame, range(0, int(total_frames + max_blocksize))), 20):
# pipe.stdin.write(_)
# sys.stderr.write('\rdone {0:%}'.format(i/(total_frames + max_blocksize)))
#p.close()

#Signle Threaded not much slower then multi-threading
if __name__ == "__main__":
 for i , _ in enumerate(range(0, int(total_frames + max_blocksize))):
 render_frame(_)
 pipe.stdin.write(render_frame(_))
 sys.stderr.write('\rdone {0:%}'.format(i/(total_frames + max_blocksize)))



-
How to create a clip from an mp4-file quickly ?
26 mars 2023, par Moritz GroßI have a web app that lets users download a clip from a mp4-file specified before. Currently I use
ffmpeg
via python like this :

os.system('ffmpeg -i original_video -ss {start} -t {duration} result_video')



Processing 10 minutes of 720p video with this method also takes a few minutes (during the execution, ffmpeg displays speed=3x on average). Does this mean processing 10 minutes of video takes 3minutes & 20 seconds as I understand it ?


Is this slow of a performance expected ? Can I improve it by using an other filetype than mp4 ?


-
Batch concation of multiple videos files (Bash)
4 janvier 2024, par pops64I have clips from multiple different scenes in the same folder I was wondering if any one had a script that groups clips belonging to each scene together than pass them into ffmpeg for a concatenation and transcode. The file name pattern is uniform. And ids are separated by a hyphen with only the scene id being unique. I am currently doing this scene by scene in FFmpeg batch av converter but any help automating this in bash or powershell would be greatly appreciated. I just can't figure out where to start


{name_of_scene}-{scene_id}-{clip_id}-{resolution}.{filetype}