You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
77 lines
2.2 KiB
Pt�on
77 lines
2.2 KiB
Pt�on
import os
|
|
import sys
|
|
import json
|
|
import argparse
|
|
import traceback
|
|
|
|
os.environ['DJANGO_SETTINGS_MODULE'] = 'cvat.settings.production'
|
|
|
|
import django
|
|
django.setup()
|
|
|
|
import numpy as np
|
|
import cv2
|
|
|
|
from cvat.apps.auto_annotation.model_manager import run_inference_engine_annotation
|
|
|
|
|
|
def _get_kwargs():
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument('--py', required=True, help='Path to the python interpt file')
|
|
parser.add_argument('--xml', required=True, help='Path to the xml file')
|
|
parser.add_argument('--bin', required=True, help='Path to the bin file')
|
|
parser.add_argument('--json', required=True, help='Path to the JSON mapping file')
|
|
parser.add_argument('--restricted', dest='restricted', action='store_true')
|
|
parser.add_argument('--unrestricted', dest='restricted', action='store_false')
|
|
parser.add_argument('--image-files', nargs='*', help='Paths to image files you want to test')
|
|
|
|
return vars(parser.parse_args())
|
|
|
|
|
|
class InterpreterError(Exception):
|
|
pass
|
|
|
|
|
|
def main():
|
|
kwargs = _get_kwargs()
|
|
|
|
py_file = kwargs['py']
|
|
bin_file = kwargs['bin']
|
|
mapping_file = kwargs['json']
|
|
xml_file = kwargs['xml']
|
|
|
|
if not os.path.isfile(py_file):
|
|
print('Py file not found! Check the path')
|
|
return
|
|
|
|
if not os.path.isfile(bin_file):
|
|
print('Bin file is not found! Check path!')
|
|
return
|
|
|
|
if not os.path.isfile(xml_file):
|
|
print('XML File not found! Check path!')
|
|
return
|
|
|
|
if not os.path.isfile(mapping_file):
|
|
print('JSON file is not found! Check path!')
|
|
return
|
|
|
|
with open(mapping_file) as json_file:
|
|
mapping = json.load(json_file)
|
|
|
|
restricted = kwargs['restricted']
|
|
image_files = kwargs.get('image_files')
|
|
print(image_files, kwargs.keys())
|
|
|
|
if image_files:
|
|
image_data = [cv2.imread(f) for f in image_files]
|
|
else:
|
|
test_image = np.ones((1024, 1980, 3), np.uint8) * 255
|
|
image_data = [test_image,]
|
|
attribute_spec = {}
|
|
results = run_inference_engine_annotation(image_data, xml_file, bin_file,mapping, attribute_spec, py_file, restricted=restricted)
|
|
print('Program Worked!')
|
|
|
|
if __name__ == '__main__':
|
|
main()
|