val set: always use all samples, even if last batch is smaller than specified batch size

src/DataLoaderIAM.py

@@ -107,24 +107,34 @@ class DataLoaderIAM:
         self.currIdx = 0
         random.shuffle(self.trainSamples)
         self.samples = self.trainSamples[:self.numTrainSamplesPerEpoch]
+        self.currSet = 'train'
 
     def validationSet(self):
         "switch to validation set"
         self.dataAugmentation = False
         self.currIdx = 0
         self.samples = self.validationSamples
+        self.currSet = 'val'
 
     def getIteratorInfo(self):
         "current batch index and overall number of batches"
-        return (self.currIdx // self.batchSize + 1, len(self.samples) // self.batchSize)
+        if self.currSet == 'train':
+            numBatches = int(np.floor(len(self.samples) / self.batchSize))  # train set: only full-sized batches
+        else:
+            numBatches = int(np.ceil(len(self.samples) / self.batchSize))  # val set: allow last batch to be smaller
+        currBatch = self.currIdx // self.batchSize + 1
+        return currBatch, numBatches
 
     def hasNext(self):
         "iterator"
-        return self.currIdx + self.batchSize <= len(self.samples)
+        if self.currSet == 'train':
+            return self.currIdx + self.batchSize <= len(self.samples)  # train set: only full-sized batches
+        else:
+            return self.currIdx < len(self.samples)  # val set: allow last batch to be smaller
 
     def getNext(self):
         "iterator"
-        batchRange = range(self.currIdx, self.currIdx + self.batchSize)
+        batchRange = range(self.currIdx, min(self.currIdx + self.batchSize, len(self.samples)))
         gtTexts = [self.samples[i].gtText for i in batchRange]
 
         imgs = []