def show(self, vidName,experimentRunNumber=0, experiment='default', delay=1):
"""Show the movie
Args:
self,vidName
Returns:
None
"""
if experiment=='default':
idx=0;
elif experiment=='TRE':
idx=1
elif experiment=='SRE':
idx=2
else:
raise NameError('Experiment: '+experiment+' does not exist, try one of these: default, TRE, SRE.')
experiment= VisualizeExperiment(self.dataset,self.experiments.data[experiment])
experiment.show(vidName,experimentRunNumber=experimentRunNumber,delay=delay)
def precisionAndSuccessPlot(self,n=1000, all=True):
d=dict()
for experimentName,experimentData in self.experiments.data.iteritems():
e=VisualizeExperiment(self.dataset,experimentData)
(x_pr, y_pr, x_s, y_s)=e.precisionAndSuccessDataAveragedPerVideo(n)
d[experimentName]= (x_pr, y_pr, x_s, y_s)
if not all:
break;
# do the plotting business here
cm = plt.get_cmap('gist_rainbow')
NUM_COLORS = len(x_pr)
titleFontSize = 16;
headerFontSize = 14;
axisFontSize = 12;
lineWidth = 1.8;
legendSize = 9;
plt.figure(figsize=(13,9),)
with plt.style.context('grayscale'):
i = 2
idx=1
for expName in d.keys():
if (not all) and (expName != 'default'):
break
(x_pr, y_pr, x_s, y_s)=d[expName]
handlesLegendPrecision = list()
handlesLegendSuccess = list()
p = np.trapz(y_pr, x=x_pr) / 51
s = np.trapz(y_s, x=x_s)
p = np.ma.round(p, 2)
s = np.ma.round(s, 2)
color = cm(1. * i / NUM_COLORS)
if idx==1:
red_patch = mpatches.Patch(label=self.experiments.data[expName].trackerLabel+' [' + str(p) + ']',
color=color)
#self.run.trackerLabel
else:
red_patch = mpatches.Patch(label=' [' + str(p) + ']',
color=color)
blue_path = mpatches.Patch(label=' [' + str(s) + ']',
color=color)
handlesLegendPrecision.append(red_patch)
handlesLegendSuccess.append(blue_path)
#plt.suptitle(expName, fontsize=titleFontSize)
plt.subplot(3, 2, idx)
plt.plot(x_s, y_s, linewidth=lineWidth, color=cm(1. * i / NUM_COLORS))
if idx==1:
plt.title('success', fontsize=headerFontSize)
plt.ylim([0, 1.1])
plt.xlim([-0.02, 1.1])
if idx == 5:
plt.xlabel('Overlap threshold', fontsize=axisFontSize)
plt.ylabel('Success rate', fontsize=axisFontSize)
idx = idx + 1
plt.legend(handles=handlesLegendSuccess, prop={'size': legendSize})
plt.grid(b=False)
plt.subplot(3, 2, idx)
plt.plot(x_pr, y_pr, linewidth=lineWidth, color=cm(1. * i / NUM_COLORS))
plt.ylim([0, 1.1])
plt.xlim([-0.5, 51])
if idx==2:
plt.title("precision", fontsize=headerFontSize)
plt.grid(b=False)
if idx==6:
plt.xlabel('Location error threshold', fontsize=axisFontSize)
plt.ylabel('Precision', fontsize=axisFontSize)
ax2 = plt.twinx()
ax2.set_ylabel(expName, color='black')
ax2.grid(b=False)
idx = idx + 1
plt.legend(handles=handlesLegendPrecision, prop={'size': legendSize}, loc=2)
plt.show()
