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import logging | |
import os | |
import tensorflow as tf | |
def set_tf_loglevel(level): | |
if level >= logging.FATAL: | |
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' | |
if level >= logging.ERROR: | |
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' | |
if level >= logging.WARNING: | |
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1' | |
else: | |
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0' | |
logging.getLogger('tensorflow').setLevel(level) | |
def img_to_tensor(path): | |
''' | |
convert images to tensor | |
args: | |
path : image file path | |
''' | |
img = tf.keras.utils.load_img( | |
path, | |
color_mode="rgb", | |
target_size=(224, 224), | |
interpolation="nearest", | |
) | |
img_arr = tf.keras.utils.img_to_array(img, data_format=None, dtype=None) | |
img = tf.expand_dims(img_arr, 0) | |
return img | |