def recognize_text(self, img, task=""):
word_list = []
print("Image Processing Started")
img_handler = ImageHandler()
words = img_handler.split_text(img, task)
for word in words:
img = cv2.cvtColor(word, cv2.COLOR_BGR2GRAY)
# img = img_handler.preprocess_normal_handwriting(img)
img = img_handler.preprocess(img, self.img_size)
word_list.append(img)
# cv2.imshow('word', word)
# cv2.waitKey(0)
print("Image Processing Finished")
print("Recognizing Text Started")
batch = Batch(None, word_list)
recognized_list = self.model.batch_test(batch)
print('Image Text: ', recognized_list)
text = ''
for i in recognized_list:
text += i + ' '
return text
def get_next(self):
labels = []
imgs = []
batch_range = range(self.current_index, self.current_index + self.batch_size)
for i in batch_range:
sample = self.samples[i]
labels.append(sample.label)
img = cv2.imread(sample.file_path, cv2.IMREAD_GRAYSCALE)
img_handler = ImageHandler()
img = img_handler.preprocess(img, self.img_size)
imgs.append(img)
self.current_index += self.batch_size
return Batch(labels, imgs)
def test_address(self, img, task=""):
word_list = []
img_handler = ImageHandler()
words = img_handler.split_text(img, task)
for word in words:
img = cv2.cvtColor(word, cv2.COLOR_BGR2GRAY)
# img = img_handler.preprocess_normal_handwriting(img)
img = img_handler.preprocess(img, self.img_size)
word_list.append(img)
# cv2.imshow('word', word)
# cv2.waitKey(0)
batch = Batch(None, word_list)
recognized_list = self.model.batch_test(batch)
return recognized_list
