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openface
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lfw-classification: Add largeFont option.

This commit is contained in:
Brandon Amos 2016-02-17 13:54:08 -05:00
parent deeb66f87d
commit b3e41133ca
1 changed files with 42 additions and 16 deletions
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58
evaluation/lfw-classification.py
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@ -67,11 +67,16 @@ def main():
help='Location of aligned LFW images')
parser.add_argument('--networkModel', type=str, help="Path to Torch network model.",
default=os.path.join(openfaceModelDir, 'nn4.small2.v1.t7'))
parser.add_argument('--largeFont', action='store_true')
parser.add_argument('workDir', type=str,
help='The work directory where intermediate files and results are kept.')
args = parser.parse_args()
# print(args)
if args.largeFont:
font = {'family': 'normal', 'size': 20}
mpl.rc('font', **font)
mkdirP(args.workDir)
print("Getting lfwPpl")
@ -104,11 +109,14 @@ def main():
cache = os.path.join(args.workDir, 'openface.gpu.svm.pkl')
openfaceGPUsvmDf = cacheToFile(cache)(openfaceExp)(lfwPpl, net, cls)
plotAccuracy(args.workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
plotAccuracy(args.workDir, args.largeFont,
eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf)
plotTrainingTime(args.workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
plotTrainingTime(args.workDir, argrs.largeFont,
eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf)
plotPredictionTime(args.workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
plotPredictionTime(args.workDir, args.largeFont,
eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf)
# http://stackoverflow.com/questions/16463582
@ -271,12 +279,15 @@ def openfaceExp(lfwAligned, net, cls):
return df
def plotAccuracy(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
def plotAccuracy(workDir, largeFont, eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf):
indices = eigenFacesDf.index.values
barWidth = 0.2
fig = plt.figure(figsize=(10, 4))
if largeFont:
fig = plt.figure(figsize=(10, 5))
else:
fig = plt.figure(figsize=(10, 4))
ax = fig.add_subplot(111)
plt.bar(indices, eigenFacesDf['accsMean'], barWidth,
yerr=eigenFacesDf['accsStd'], label='Eigenfaces',
@ -292,9 +303,14 @@ def plotAccuracy(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
color=colors[3], ecolor='0.3', alpha=alpha)
box = ax.get_position()
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.85])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4,
fancybox=True, shadow=True)
if largeFont:
ax.set_position([box.x0, box.y0 + 0.07, box.width, box.height * 0.83])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4,
fancybox=True, shadow=True, fontsize=16)
else:
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.85])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4,
fancybox=True, shadow=True)
plt.ylabel("Classification Accuracy")
plt.xlabel("Number of People")
@ -309,7 +325,7 @@ def plotAccuracy(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
plt.savefig(os.path.join(workDir, 'accuracies.png'))
def plotTrainingTime(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
def plotTrainingTime(workDir, largeFont, eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf):
indices = eigenFacesDf.index.values
barWidth = 0.2
@ -331,9 +347,14 @@ def plotTrainingTime(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
color=colors[3], ecolor='0.3', alpha=alpha)
box = ax.get_position()
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.85])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4,
fancybox=True, shadow=True)
if largeFont:
ax.set_position([box.x0, box.y0 + 0.08, box.width, box.height * 0.83])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.27), ncol=4,
fancybox=True, shadow=True, fontsize=16)
else:
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.85])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4,
fancybox=True, shadow=True)
plt.ylabel("Training Time (s)")
plt.xlabel("Number of People")
@ -350,7 +371,7 @@ def plotTrainingTime(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
plt.savefig(os.path.join(workDir, 'trainTimes.png'))
def plotPredictionTime(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
def plotPredictionTime(workDir, largeFont, eigenFacesDf, fishFacesDf, lbphFacesDf,
openfaceCPUsvmDf, openfaceGPUsvmDf):
indices = eigenFacesDf.index.values
barWidth = 0.15
@ -376,9 +397,14 @@ def plotPredictionTime(workDir, eigenFacesDf, fishFacesDf, lbphFacesDf,
color=colors[4], ecolor='0.3', alpha=alpha)
box = ax.get_position()
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.77])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.37), ncol=3,
fancybox=True, shadow=True)
if largeFont:
ax.set_position([box.x0, box.y0 + 0.11, box.width, box.height * 0.7])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.45), ncol=3,
fancybox=True, shadow=True, fontsize=16)
else:
ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.77])
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.37), ncol=3,
fancybox=True, shadow=True)
plt.ylabel("Prediction Time (s)")
plt.xlabel("Number of People")
ax.set_xticks(indices + 2.5 * barWidth)