def test_train():
"""Test training
use nvidia-smi -i 5 -l 5 to monitor GPU
-i GPU device number -l interval to refresh
"""
# load cutomized conf
conf = DIFFERNET_CONF
logger.info(f"working folder: {conf.get('differnet_work_dir')}")
differnetutil = DiffernetUtil(conf, "black1")
# train the model
differnetutil.train_model()
def test_model():
"""Test training"""
# load cutomized conf
conf = DIFFERNET_CONF
logger.info(f"working folder: {conf.get('differnet_work_dir')}")
differnetutil = DiffernetUtil(conf, "black1")
t1 = time.process_time()
# test trained model
differnetutil.test_model()
t2 = time.process_time()
elapsed_time = t2 - t1
logger.info(f"elapsed time: {elapsed_time}")
def test_detect(self):
"""Test Detection"""
# load cutomized conf
conf = DIFFERNET_CONF
logger.info(f"working folder: {conf.get('differnet_work_dir')}")
t0 = time.process_time()
differnetutil = DiffernetUtil(conf, "black1")
differnetutil.load_model()
t1 = time.process_time()
elapsed_time = t1 - t0
logger.info(f"Model load elapsed time: {elapsed_time}")
img = cv2.imread(
os.path.join(
differnetutil.test_dir, "defect", "Camera0_202009142018586_product.png"
),
cv2.IMREAD_UNCHANGED,
)
t1 = time.process_time()
ret = differnetutil.detect(img, 10)
# calculate time
t2 = time.process_time()
elapsed_time = t2 - t1
logger.info(f"Detection elapsed time: {elapsed_time}")
assert ret == True
img = cv2.imread(
os.path.join(
differnetutil.test_dir, "good", "Camera0_202009142018133_product.png"
),
cv2.IMREAD_UNCHANGED,
)
t2 = time.process_time()
ret = differnetutil.detect(img, 10)
t3 = time.process_time()
elapsed_time = t3 - t2
logger.info(f"Detection elapsed time: {elapsed_time}")
assert ret == False