def validate(model, loader):
"validate NN"
loader.validationSet()
numCharErr = 0
numCharTotal = 0
numWordOK = 0
numWordTotal = 0
totalCER = []
totalWER = []
while loader.hasNext():
iterInfo = loader.getIteratorInfo()
print('Batch:', iterInfo[0], '/', iterInfo[1])
batch = loader.getNext()
recognized = model.inferBatch(batch)
print('Ground truth -> Recognized')
for i in range(len(recognized)):
numWordOK += 1 if batch.gtTexts[i] == recognized[i] else 0
numWordTotal += 1
dist = editdistance.eval(recognized[i], batch.gtTexts[i])
currCER = dist / max(len(recognized[i]), len(batch.gtTexts[i]))
totalCER.append(currCER)
currWER = wer(recognized[i].split(), batch.gtTexts[i].split())
totalWER.append(currWER)
numCharErr += dist
numCharTotal += len(batch.gtTexts[i])
print('[OK]' if dist == 0 else '[ERR:%d]' % dist,
'"' + batch.gtTexts[i] + '"', '->',
'"' + recognized[i] + '"')
# print validation result
try:
charErrorRate = sum(totalCER) / len(totalCER)
wordErrorRate = sum(totalWER) / len(totalWER)
textLineAccuracy = numWordOK / numWordTotal
except ZeroDivisionError:
charErrorRate = 0
wordErrorRate = 0
textLineAccuracy = 0
print(
'Character error rate: %f%%. Text line accuracy: %f%%. Word error rate: %f%%'
% (charErrorRate * 100.0, textLineAccuracy * 100.0,
wordErrorRate * 100.0))
return charErrorRate, textLineAccuracy, wordErrorRate
def validate(model, loader):
""" Validate neural network """
print('Validate neural network')
loader.validationSet()
numCharErr = 0
numCharTotal = 0
numWordOK = 0
numWordTotal = 0
totalCER = []
totalWER = []
while loader.hasNext():
iterInfo = loader.getIteratorInfo()
print('Batch:', iterInfo[0], '/', iterInfo[1])
batch = loader.getNext()
recognized = model.inferBatch(batch)
print('Ground truth -> Recognized')
for i in range(len(recognized)):
numWordOK += 1 if batch.gtTexts[i] == recognized[i] else 0
print("NumOK..", numWordOK)
numWordTotal += 1
dist = editdistance.eval(recognized[i], batch.gtTexts[i])
## editdistance
currCER = dist / max(len(recognized[i]), len(batch.gtTexts[i]))
totalCER.append(currCER)
currWER = wer(recognized[i].split(), batch.gtTexts[i].split())
totalWER.append(currWER)
numCharErr += dist
numCharTotal += len(batch.gtTexts[i])
print('[OK]' if dist == 0 else '[ERR:%d]' % dist,
'"' + batch.gtTexts[i] + '"', '->',
'"' + recognized[i] + '"')
# Print validation result
charErrorRate = sum(totalCER) / len(totalCER)
addressAccuracy = numWordOK / numWordTotal
wordErrorRate = sum(totalWER) / len(totalWER)
print(
'Character error rate: %f%%. Address accuracy: %f%%. Word error rate: %f%%'
% (charErrorRate * 100.0, addressAccuracy * 100.0,
wordErrorRate * 100.0))
return charErrorRate, addressAccuracy, wordErrorRate
