def printCategoryScores(scoreDict, instScoreDict, args):
if (args.quiet):
return
print(args.bold + 'categories IoU nIoU' + args.nocol)
print('--------------------------------')
for categoryName in scoreDict:
if all(label.ignoreInEval for label in category2labels[categoryName]):
continue
iouStr = getColorEntry(scoreDict[categoryName],
args) + '{val:>5.3f}'.format(
val=scoreDict[categoryName]) + args.nocol
niouStr = getColorEntry(
instScoreDict[categoryName], args) + '{val:>5.3f}'.format(
val=instScoreDict[categoryName]) + args.nocol
print('{:<14}: '.format(categoryName) + iouStr + ' ' + niouStr)
def printClassScores(scoreList, instScoreList, args):
if (args.quiet):
return
print(args.bold + 'classes IoU nIoU' + args.nocol)
print('--------------------------------')
for label in args.evalLabels:
if (id2label[label].ignoreInEval):
continue
labelName = str(id2label[label].name)
iouStr = getColorEntry(
scoreList[labelName],
args) + '{val:>5.3f}'.format(val=scoreList[labelName]) + args.nocol
niouStr = getColorEntry(instScoreList[labelName],
args) + '{val:>5.3f}'.format(
val=instScoreList[labelName]) + args.nocol
print('{:<14}: '.format(labelName) + iouStr + ' ' + niouStr)
def evaluateImgLists(predictionImgList, groundTruthImgList, args):
if len(predictionImgList) != len(groundTruthImgList):
printError(
'List of images for prediction and groundtruth are not of equal size.'
)
confMatrix = generateMatrix(args)
instStats = generateInstanceStats(args)
perImageStats = {}
nbPixels = 0
if not args.quiet:
print('Evaluating {} pairs of images...'.format(
len(predictionImgList)))
# Evaluate all pairs of images and save them into a matrix
for i in range(len(predictionImgList)):
predictionImgFileName = predictionImgList[i]
groundTruthImgFileName = groundTruthImgList[i]
#print 'Evaluate ', predictionImgFileName, '<>', groundTruthImgFileName
nbPixels += evaluatePair(predictionImgFileName, groundTruthImgFileName,
confMatrix, instStats, perImageStats, args)
# sanity check
if confMatrix.sum() != nbPixels:
printError(
'Number of analyzed pixels and entries in confusion matrix disagree: contMatrix {}, pixels {}'
.format(confMatrix.sum(), nbPixels))
if not args.quiet:
print('\rImages Processed: {}'.format(i + 1), end=' ')
sys.stdout.flush()
if not args.quiet:
print('\n')
# sanity check
if confMatrix.sum() != nbPixels:
printError(
'Number of analyzed pixels and entries in confusion matrix disagree: contMatrix {}, pixels {}'
.format(confMatrix.sum(), nbPixels))
# print confusion matrix
if (not args.quiet):
printConfMatrix(confMatrix, args)
# Calculate IOU scores on class level from matrix
classScoreList = {}
for label in args.evalLabels:
labelName = id2label[label].name
classScoreList[labelName] = getIouScoreForLabel(
label, confMatrix, args)
# Calculate instance IOU scores on class level from matrix
classInstScoreList = {}
for label in args.evalLabels:
labelName = id2label[label].name
classInstScoreList[labelName] = getInstanceIouScoreForLabel(
label, confMatrix, instStats, args)
# Print IOU scores
if (not args.quiet):
print('')
print('')
printClassScores(classScoreList, classInstScoreList, args)
iouAvgStr = getColorEntry(getScoreAverage(
classScoreList, args), args) + '{avg:5.3f}'.format(
avg=getScoreAverage(classScoreList, args)) + args.nocol
niouAvgStr = getColorEntry(getScoreAverage(
classInstScoreList, args), args) + '{avg:5.3f}'.format(
avg=getScoreAverage(classInstScoreList, args)) + args.nocol
print('--------------------------------')
print('Score Average : ' + iouAvgStr + ' ' + niouAvgStr)
print('--------------------------------')
print('')
# Calculate IOU scores on category level from matrix
categoryScoreList = {}
for category in category2labels.keys():
categoryScoreList[category] = getIouScoreForCategory(
category, confMatrix, args)
# Calculate instance IOU scores on category level from matrix
categoryInstScoreList = {}
for category in category2labels.keys():
categoryInstScoreList[category] = getInstanceIouScoreForCategory(
category, confMatrix, instStats, args)
# Print IOU scores
if (not args.quiet):
print('')
printCategoryScores(categoryScoreList, categoryInstScoreList, args)
iouAvgStr = getColorEntry(getScoreAverage(
categoryScoreList, args), args) + '{avg:5.3f}'.format(
avg=getScoreAverage(categoryScoreList, args)) + args.nocol
niouAvgStr = getColorEntry(
getScoreAverage(categoryInstScoreList, args),
args) + '{avg:5.3f}'.format(
avg=getScoreAverage(categoryInstScoreList, args)) + args.nocol
print('--------------------------------')
print('Score Average : ' + iouAvgStr + ' ' + niouAvgStr)
print('--------------------------------')
print('')
allResultsDict = createResultDict(confMatrix, classScoreList,
classInstScoreList, categoryScoreList,
categoryInstScoreList, perImageStats,
args)
# write result file
if args.JSONOutput:
writeJSONFile(allResultsDict, args)
writeDict2Txt(allResultsDict, 'results.txt')
# return confusion matrix
return allResultsDict
def printConfMatrix(confMatrix, args):
# print line
print('\b{text:{fill}>{width}}'.format(width=15, fill='-', text=' '),
end=' ')
for label in args.evalLabels:
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 2,
fill='-',
text=' '),
end=' ')
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 3,
fill='-',
text=' '))
# print label names
print('\b{text:>{width}} |'.format(width=13, text=''), end=' ')
for label in args.evalLabels:
print('\b{text:^{width}} |'.format(width=args.printRow,
text=id2label[label].name[0]),
end=' ')
print('\b{text:>{width}} |'.format(width=6, text='Prior'))
# print line
print('\b{text:{fill}>{width}}'.format(width=15, fill='-', text=' '),
end=' ')
for label in args.evalLabels:
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 2,
fill='-',
text=' '),
end=' ')
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 3,
fill='-',
text=' '))
# print matrix
for x in range(0, confMatrix.shape[0]):
if (not x in args.evalLabels):
continue
# get prior of this label
prior = getPrior(x, confMatrix)
# skip if label does not exist in ground truth
if prior < 1e-9:
continue
# print name
name = id2label[x].name
if len(name) > 13:
name = name[:13]
print('\b{text:>{width}} |'.format(width=13, text=name), end=' ')
# print matrix content
for y in range(0, len(confMatrix[x])):
if (not y in args.evalLabels):
continue
matrixFieldValue = getMatrixFieldValue(confMatrix, x, y, args)
print(getColorEntry(matrixFieldValue, args) +
'\b{text:>{width}.2f} '.format(
width=args.printRow, text=matrixFieldValue) + args.nocol,
end=' ')
# print prior
print(
getColorEntry(prior, args) +
'\b{text:>{width}.4f} '.format(width=6, text=prior) + args.nocol)
# print line
print('\b{text:{fill}>{width}}'.format(width=15, fill='-', text=' '),
end=' ')
for label in args.evalLabels:
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 2,
fill='-',
text=' '),
end=' ')
print('\b{text:{fill}>{width}}'.format(width=args.printRow + 3,
fill='-',
text=' '),
end=' ')
