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• Revision 176c291d9c : Fix potential overflow issue in hadamard_16x16() This commit fixes a potential

  12 juin 2015, par Jingning Han

  Changed Paths :
   Modify /vp9/encoder/vp9_avg.c

  
   Modify /vp9/encoder/x86/vp9_avg_intrin_sse2.c

  
  
  Fix potential overflow issue in hadamard_16x16()

  This commit fixes a potential integer overflow issue in function
  hadamard_16x16. It adds corresponding dynamic range comment.

  Change-Id : Iec22f3be345fb920ec79178e016378e2f65b20be

• HLS for on demand streaming

  15 septembre 2017, par Awais fiaz

  I have been working on DASH (Dynamic adaptive streaming over http) in the past but as DASH is not supported on IOS based devices so i am moving to HLS (http live streaming) as it works on all devices.

  I am in need of a guide of HLS for on demand streaming to understand encoding flow and techniques being used in this process.

  i am using FFMPEG as encoding library PHP for server side scripting and apache2 as server.

  any help regarding this would be really appreciated thanks.

• Matplotlib use Ffmpeg to save plot to be mp4 not include full step

  21 décembre 2020, par 昌翰余

  I use ffmpeg to store the dynamic graph drawn on matplotlib, but the output file is only 2 seconds
but It should have been 30 seconds.
I set a graph to run three curves, a total of 30 seconds of data,
the graph that ran on the py file is normal,
but the output is only the first two seconds of the output.
May I ask if I missed something

  


  Below is my code

  


  import matplotlib.pyplot as plt
from matplotlib import animation
from numpy import random 
import pandas as pd
from matplotlib.animation import FFMpegWriter

FFwriter=animation.FFMpegWriter(fps=30, extra_args=['-vcodec', 'libx264'])
data = pd.read_csv('apple1.csv', delimiter = ',', dtype = None)
data = data.values
AccX1=[]
AccY1=[]
AccZ1=[]
AccX2=[]
AccY2=[]
AccZ2=[]

time = []

for i in range(600):
        AccX1.append(data[i][8])
        AccY1.append(data[i][9])
        AccZ1.append(data[i][10])
        AccX2.append(data[i][24])
        AccY2.append(data[i][25])
        AccZ2.append(data[i][26])
        
        time.append(data[i][0])
        
fig = plt.figure()
ax1 = plt.axes(xlim=(0,3000), ylim=(6,-6))
line, = ax1.plot([], [], lw=2)
plt.xlabel('ACC')
plt.ylabel('Time')

plotlays, plotcols = [3], ["r","g","b"]
lines = []
for index in range(3):
    lobj = ax1.plot([],[],lw=2,color=plotcols[index])[0]
    lines.append(lobj)


def init():
    for line in lines:
        line.set_data([],[])
    return lines

x1,y1 = [],[]
x2,y2 = [],[]
x3,y3 = [],[]



i=0

def animate(frame):
    global i
    
    i+=1
    x = i
    y = AccX1[i]

    x1.append(x)
    y1.append(y)

    x = i
    y = AccY1[i]
    x2.append(x)
    y2.append(y)

    x = i
    y = AccZ1[i]
    x3.append(x)
    y3.append(y)
    

    xlist = [x1, x2,x3]
    ylist = [y1, y2,y3]


    for lnum,line in enumerate(lines):
        line.set_data(xlist[lnum], ylist[lnum]) 


    return lines


anim = animation.FuncAnimation(fig, animate,
                    init_func=init, blit=True,interval=10)
anim.save('test.mp4',writer=FFwriter)
plt.show()


  


  The dynamic picture ran out using plt.show is correct.
And I don't think I have set the length of storage. Did I add something ?