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109 lines
4.7 KiB
Python
109 lines
4.7 KiB
Python
import sys
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import os
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import cv2 as cv
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def add_argument(zoo, parser, name, help, required=False, default=None, type=None, action=None, nargs=None):
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if len(sys.argv) <= 1:
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return
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modelName = sys.argv[1]
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if os.path.isfile(zoo):
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fs = cv.FileStorage(zoo, cv.FILE_STORAGE_READ)
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node = fs.getNode(modelName)
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if not node.empty():
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value = node.getNode(name)
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if not value.empty():
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if value.isReal():
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default = value.real()
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elif value.isString():
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default = value.string()
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elif value.isInt():
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default = int(value.real())
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elif value.isSeq():
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default = []
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for i in range(value.size()):
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v = value.at(i)
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if v.isInt():
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default.append(int(v.real()))
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elif v.isReal():
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default.append(v.real())
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else:
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print('Unexpected value format')
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exit(0)
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else:
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print('Unexpected field format')
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exit(0)
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required = False
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if action == 'store_true':
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default = 1 if default == 'true' else (0 if default == 'false' else default)
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assert(default is None or default == 0 or default == 1)
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parser.add_argument('--' + name, required=required, help=help, default=bool(default),
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action=action)
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else:
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parser.add_argument('--' + name, required=required, help=help, default=default,
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action=action, nargs=nargs, type=type)
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def add_preproc_args(zoo, parser, sample):
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aliases = []
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if os.path.isfile(zoo):
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fs = cv.FileStorage(zoo, cv.FILE_STORAGE_READ)
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root = fs.root()
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for name in root.keys():
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model = root.getNode(name)
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if model.getNode('sample').string() == sample:
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aliases.append(name)
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parser.add_argument('alias', nargs='?', choices=aliases,
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help='An alias name of model to extract preprocessing parameters from models.yml file.')
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add_argument(zoo, parser, 'model', required=True,
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help='Path to a binary file of model contains trained weights. '
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'It could be a file with extensions .caffemodel (Caffe), '
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'.pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet), .bin (OpenVINO)')
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add_argument(zoo, parser, 'config',
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help='Path to a text file of model contains network configuration. '
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'It could be a file with extensions .prototxt (Caffe), .pbtxt or .config (TensorFlow), .cfg (Darknet), .xml (OpenVINO)')
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add_argument(zoo, parser, 'mean', nargs='+', type=float, default=[0, 0, 0],
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help='Preprocess input image by subtracting mean values. '
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'Mean values should be in BGR order.')
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add_argument(zoo, parser, 'scale', type=float, default=1.0,
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help='Preprocess input image by multiplying on a scale factor.')
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add_argument(zoo, parser, 'width', type=int,
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help='Preprocess input image by resizing to a specific width.')
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add_argument(zoo, parser, 'height', type=int,
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help='Preprocess input image by resizing to a specific height.')
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add_argument(zoo, parser, 'rgb', action='store_true',
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help='Indicate that model works with RGB input images instead BGR ones.')
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add_argument(zoo, parser, 'classes',
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help='Optional path to a text file with names of classes to label detected objects.')
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def findFile(filename):
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if filename:
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if os.path.exists(filename):
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return filename
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samplesDataDir = os.path.join(os.path.dirname(os.path.abspath(__file__)),
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'..',
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'data',
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'dnn')
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if os.path.exists(os.path.join(samplesDataDir, filename)):
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return os.path.join(samplesDataDir, filename)
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for path in ['OPENCV_DNN_TEST_DATA_PATH', 'OPENCV_TEST_DATA_PATH']:
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try:
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extraPath = os.environ[path]
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absPath = os.path.join(extraPath, 'dnn', filename)
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if os.path.exists(absPath):
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return absPath
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except KeyError:
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pass
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print('File ' + filename + ' not found! Please specify a path to '
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'/opencv_extra/testdata in OPENCV_DNN_TEST_DATA_PATH environment '
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'variable or pass a full path to model.')
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exit(0)
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