def getNext(self):
""" Iterator """
batchRange = range(self.currIdx, self.currIdx + self.batchSize)
gtTexts = [self.samples[i].gtText for i in batchRange]
imgs = [preprocessor(self.samples[i].filePath,
self.imgSize, binary=True) for i in batchRange]
self.currIdx += self.batchSize
return Batch(gtTexts, imgs)
def infer(model, fnImg):
""" Recognize text in image provided by file path """
img = preprocessor(fnImg, model.imgSize, binary=True)
# Fill all batch elements with same input image
batch = Batch(None, [img] * Model.batchSize)
recognized = model.inferBatch(batch) # recognize text
# All batch elements hold same result
print('Recognized:', '"' + recognized[0] + '"')
def infer(model, paths):
""" Recognize text in image provided by file path """
imgs = [
preprocessor(paths[i], model.imgSize, binary=True)
for i in range(len(paths))
]
if len(imgs) >= Model.batchSize:
imgs = imgs[0:Model.batchSize]
else: # len(imgs) <= Model.batchSize
imgs = imgs + ([imgs[0]] * (Model.batchSize - len(imgs)))
# Fill all batch elements with same input image
batch = Batch(["blah"] * Model.batchSize, imgs)
recognized = model.inferBatch(batch) # recognize text
# All batch elements hold same result
for i in range(min(len(paths), len(recognized))):
print('Recognized:', paths[i], 'as "' + recognized[i] + '"')