def main(_):
print(FLAGS.mode)
if FLAGS.mode == "train":
train()
elif FLAGS.mode == 'validation':
dct = validation()
result_file = 'result.dict'
logger.info('Write result into {0}'.format(result_file))
with open(result_file, 'wb') as f:
pickle.dump(dct, f)
logger.info('Write file ends')
elif FLAGS.mode == 'inference':
label_dict = get_label_dict()
name_list = get_file_list('./tmp/')
#binary_pic(name_list)
#tmp_name_list = get_file_list('../data/tmp')
# 將待預測的圖片名字列表送入predict()進行預測，得到預測的結果及其index
final_predict_val, final_predict_index = inference(name_list)
final_reco_text = [] # 儲存最後識別出來的文字串
# 給出top 3預測，candidate1是機率最高的預測
for i in range(len(final_predict_val)):
candidate1 = final_predict_index[i][0][0]
candidate2 = final_predict_index[i][0][1]
candidate3 = final_predict_index[i][0][2]
final_reco_text.append(label_dict[int(candidate1)])
logger.info(
'[the result info] image: {0} predict: {1} {2} {3}; predict index {4} predict_val {5}'
.format(name_list[i], label_dict[int(candidate1)],
label_dict[int(candidate2)],
label_dict[int(candidate3)], final_predict_index[i],
final_predict_val[i]))
print('=====================OCR RESULT=======================\n')
# 印出所有識別出來的結果（取top 1）
f = open('./result/outcome.txt', 'r+', encoding="utf-8-sig")
f.truncate()
for i in range(len(final_reco_text)):
print(final_reco_text[i], end=" ")
with open('./result/outcome.txt', 'a+', encoding="utf-8-sig") as f:
f.write("%s" % final_reco_text[i])
time.sleep(1)
outcome('./result/outcome.txt')
def run(self):
if self.device.isOpened():
try:
while True:
ret, frame = self.device.read()
height, width, bytesPerComponent = frame.shape
bytesPerLine = bytesPerComponent * width
# 變換彩色空間順序
cv2.cvtColor(frame, cv2.COLOR_BGR2RGB, frame)
# 轉為QImage物件
image = QImage(frame.data, width, height, bytesPerLine,
QImage.Format_RGB888)
if self.paizhao == 1:
image.save('./origin/takephoto.png')
self.paizhao = 0
pixmap = QPixmap.fromImage(image)
pixmap = pixmap.scaled(400, 300,
QtCore.Qt.KeepAspectRatio)
self.imgLab.setPixmap(pixmap)
objectdetection()
outcome('./result/audio/objoutcome.txt')
finally:
self.device.release()
def run():
#print(command)
c = command()
if c == "閱讀" or c == "閱讀模式":
takephoto()
notblurry()
ocr()
outcome('./result/audio/outcome.txt')
elif c == "用餐" or c == "用餐模式":
takephoto()
objectdetection()
outcome('./result/audio/objoutcome.txt')
elif c == "沒事" or c == "結束":
return 0
else:
outcome('./result/audio/responsenoidea.txt')