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Open Source Computer Vision Library
https://opencv.org/
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108 lines
4.7 KiB
108 lines
4.7 KiB
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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