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136 lines
4.5 KiB
Python
136 lines
4.5 KiB
Python
import os
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import json
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import argparse
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import random
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import logging
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os.environ['DJANGO_SETTINGS_MODULE'] = 'cvat.settings.production'
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import django
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django.setup()
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import numpy as np
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import cv2
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from cvat.apps.auto_annotation.model_manager import run_inference_engine_annotation
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def _get_kwargs():
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parser = argparse.ArgumentParser()
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parser.add_argument('--py', required=True, help='Path to the python interpt file')
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parser.add_argument('--xml', required=True, help='Path to the xml file')
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parser.add_argument('--bin', required=True, help='Path to the bin file')
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parser.add_argument('--json', required=True, help='Path to the JSON mapping file')
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parser.add_argument('--restricted', dest='restricted', action='store_true')
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parser.add_argument('--unrestricted', dest='restricted', action='store_false')
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parser.add_argument('--image-files', nargs='*', help='Paths to image files you want to test')
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parser.add_argument('--show-images', action='store_true', help='Show the results of the annotation in a window')
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parser.add_argument('--show-image-delay', default=0, type=int, help='Displays the images for a set duration in milliseconds, default is until a key is pressed')
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return vars(parser.parse_args())
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def random_color():
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rgbl=[255,0,0]
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random.shuffle(rgbl)
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return tuple(rgbl)
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def pairwise(iterable):
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result = []
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for i in range(0, len(iterable) - 1, 2):
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result.append((iterable[i], iterable[i+1]))
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return np.array(result, dtype=np.int32)
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def main():
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kwargs = _get_kwargs()
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py_file = kwargs['py']
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bin_file = kwargs['bin']
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mapping_file = kwargs['json']
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xml_file = kwargs['xml']
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if not os.path.isfile(py_file):
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logging.critical('Py file not found! Check the path')
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return
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if not os.path.isfile(bin_file):
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logging.critical('Bin file is not found! Check path!')
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return
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if not os.path.isfile(xml_file):
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logging.critical('XML File not found! Check path!')
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return
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if not os.path.isfile(mapping_file):
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logging.critical('JSON file is not found! Check path!')
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return
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with open(mapping_file) as json_file:
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mapping = json.load(json_file)
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try:
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mapping = mapping['label_map']
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except KeyError:
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logging.critical("JSON Mapping file must contain key `label_map`!")
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logging.critical("Exiting")
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return
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mapping = {int(k): v for k, v in mapping.items()}
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restricted = kwargs['restricted']
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image_files = kwargs.get('image_files')
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if image_files:
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image_data = [cv2.imread(f) for f in image_files]
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else:
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test_image = np.ones((1024, 1980, 3), np.uint8) * 255
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image_data = [test_image,]
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attribute_spec = {}
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results = run_inference_engine_annotation(image_data,
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xml_file,
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bin_file,
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mapping,
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attribute_spec,
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py_file,
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restricted=restricted)
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logging.warning('Program didn\'t have any errors.')
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show_images = kwargs.get('show_images', False)
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if show_images:
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if image_files is None:
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logging.critical("Warning, no images provided!")
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logging.critical('Exiting without presenting results')
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return
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if not results['shapes']:
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logging.warning(str(results))
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logging.critical("No objects detected!")
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return
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show_image_delay = kwargs['show_image_delay']
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for index, data in enumerate(image_data):
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for detection in results['shapes']:
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if not detection['frame'] == index:
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continue
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points = detection['points']
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# Cv2 doesn't like floats for drawing
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points = [int(p) for p in points]
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color = random_color()
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if detection['type'] == 'rectangle':
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cv2.rectangle(data, (points[0], points[1]), (points[2], points[3]), color, 3)
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elif detection['type'] in ('polygon', 'polyline'):
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# polylines is picky about datatypes
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points = pairwise(points)
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cv2.polylines(data, [points], 1, color)
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cv2.imshow(str(index), data)
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cv2.waitKey(show_image_delay)
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cv2.destroyWindow(str(index))
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if __name__ == '__main__':
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main()
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