def init():
bot_id = '1437569240:AAEd2sZ0faC1EwPvQGJPPW4xf7ohP1hTzV8'
updater = Updater(bot_id)
updater.setPhotoHandler(imageHandler)
QualityChecker.init()
ShoeDetector.init()
FeatureExtractor.init()
data_structure = Indexer.build_data_structure(config.DATASET_PATH)
Matcher.init(data_structure)
print("Bot is running...")
updater.start()
detector_model_path = 'models/model_frcnn.hdf5'
model_rpn.load_weights(detector_model_path, by_name=True)
model_classifier.load_weights(detector_model_path, by_name=True)
# COMPILE MODEL
model_rpn.compile(optimizer='sgd', loss='mse')
model_classifier.compile(optimizer='sgd', loss='mse')
# LOAD PREDICTION MODEL
classifier_model_path = 'models/MobileNetV2_192_NoCar.h5'
classifier = load_model(classifier_model_path)
# SETUP BOT AND FOLDERS
alphabeth = [
'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'L', 'M', 'N', 'O', 'P', 'Q',
'R', 'S', 'T', 'U', 'V', 'Z'
]
if not os.path.exists("res"):
os.makedirs("res")
classif_input = 192
marker_true = cv2.imread("V_tick.png", -1)
marker_false = cv2.imread("X_tick.png", -1)
bot_id = '*********'
updater = Updater(bot_id)
updater.setPhotoHandler(imageHandler)
print('---------- BOT IS READY')
updater.start()
