def main():
args = parseArgs()
print args
argv = ['', args.groundTruth, args.predictions]
print "Loading data"
gtFramesAll, prFramesAll = eval_helpers.load_data_dir(argv)
print "# gt frames :", len(gtFramesAll)
print "# pred frames:", len(prFramesAll)
if (not os.path.exists(args.outputDir)):
os.makedirs(args.outputDir)
if (args.evalPoseEstimation):
#####################################################
# evaluate per-frame multi-person pose estimation (AP)
# compute AP
print "Evaluation of per-frame multi-person pose estimation"
apAll, preAll, recAll = evaluateAP(gtFramesAll, prFramesAll,
args.outputDir, True,
args.saveEvalPerSequence)
# print AP
print "Average Precision (AP) metric:"
eval_helpers.printTable(apAll)
if (args.evalPoseTracking):
#####################################################
# evaluate multi-person pose tracking in video (MOTA)
# compute MOTA
print "Evaluation of video-based multi-person pose tracking"
metricsAll, metricsMidAll = evaluateTracking(gtFramesAll, prFramesAll,
args.outputDir, True,
args.saveEvalPerSequence)
metrics = np.zeros([Joint().count + 4, 1])
for i in range(Joint().count + 1):
metrics[i, 0] = metricsAll['mota'][0, i]
metrics[Joint().count + 1, 0] = metricsAll['motp'][0, Joint().count]
metrics[Joint().count + 2, 0] = metricsAll['pre'][0, Joint().count]
metrics[Joint().count + 3, 0] = metricsAll['rec'][0, Joint().count]
# print AP
print "Multiple Object Tracking (MOT) metrics:"
eval_helpers.printTable(metrics, motHeader=True)
eval_helpers.printStatistics(metricsMidAll)
def main():
args = parseArgs()
print args
argv = ['',args.groundTruth,args.predictions]
print "Loading data"
gtFramesAll,prFramesAll = eval_helpers.load_data_dir(argv)
print "# gt frames :", len(gtFramesAll)
print "# pred frames:", len(prFramesAll)
if (args.evalPoseEstimation):
#####################################################
# evaluate per-frame multi-person pose estimation (AP)
# compute AP
print "Evaluation of per-frame multi-person pose estimation"
apAll,preAll,recAll = evaluateAP(gtFramesAll,prFramesAll)
# print AP
print "Average Precision (AP) metric:"
eval_helpers.printTable(apAll)
if (args.evalPoseTracking):
#####################################################
# evaluate multi-person pose tracking in video (MOTA)
# compute MOTA
print "Evaluation of video-based multi-person pose tracking"
metricsAll = evaluateTracking(gtFramesAll,prFramesAll, args.trackUpperBound)
metrics = np.zeros([Joint().count + 4,1])
for i in range(Joint().count+1):
metrics[i,0] = metricsAll['mota'][0,i]
metrics[Joint().count+1,0] = metricsAll['motp'][0,Joint().count]
metrics[Joint().count+2,0] = metricsAll['pre'][0,Joint().count]
metrics[Joint().count+3,0] = metricsAll['rec'][0,Joint().count]
# print AP
print "Multiple Object Tracking (MOT) metrics:"
eval_helpers.printTable(metrics,motHeader=True)
