import os
from glob import glob
from _paths import nomeroff_net_dir
from nomeroff_net import pipeline
from nomeroff_net.tools import unzip
if __name__ == '__main__':
multiline_number_plate_detection_and_reading = pipeline(
"multiline_number_plate_detection_and_reading", image_loader="opencv")
result = multiline_number_plate_detection_and_reading(
glob(
os.path.join(nomeroff_net_dir,
'./data/examples/multiline_images/*')))
(images, images_bboxs, images_points, images_zones, region_ids,
region_names, count_lines, confidences, texts) = unzip(result)
print(texts)
"""
python3 examples/py/inference/get_started-demo2.py
"""
import os
from _paths import nomeroff_net_dir
from nomeroff_net import pipeline
from nomeroff_net.tools import unzip
if __name__ == '__main__':
number_plate_detection_and_reading = pipeline("number_plate_detection_and_reading_v2",
image_loader="opencv")
(images, images_bboxs,
images_points, images_zones, region_ids,
region_names, count_lines,
confidences, texts) = number_plate_detection_and_reading([
os.path.join(nomeroff_net_dir, './data/examples/oneline_images/example1.jpeg'),
])
# (['AC4921CB'], ['RP70012', 'JJF509'])
print(texts)
import warnings
import os
from glob import glob
from _paths import nomeroff_net_dir
from nomeroff_net import pipeline
warnings.filterwarnings("ignore")
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
if __name__ == '__main__':
number_plate_detection_and_reading = pipeline(
"number_plate_detection_and_reading_runtime",
image_loader="opencv" # Try 'turbo' for faster performance.
)
num_run = 1
batch_size = 1
num_workers = 1
images = glob(
os.path.join(nomeroff_net_dir,
"./data/examples/benchmark_oneline_np_images/1.jpeg"))
number_plate_detection_and_reading.clear_stat()
for i in range(num_run):
print(f"pass {i}")
outputs = number_plate_detection_and_reading(images,
batch_size=batch_size,
num_workers=num_workers)