Searched refs:ndarray (Results 1 – 7 of 7) sorted by relevance
| /cts/apps/CameraITS/utils/ |
| D | ip_chart_pattern_detector.py | 84 def __init__(self, feature_type: TestChartFeature, image: np.ndarray = None): argument
104 image: np.ndarray = None, argument
128 test_chart_color_bgr: np.ndarray, argument
129 image: np.ndarray = None, argument
150 image: np.ndarray = None, argument
180 test_chart_color_bgr: np.ndarray, argument
181 image: np.ndarray = None, argument
199 image: str | np.ndarray, argument
200 ) -> (np.ndarray, str):
216 if not isinstance(image, np.ndarray):
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| D | noise_model_utils.py | 67 def check_noise_model_shape(noise_model: np.ndarray) -> None: argument
86 noise_model: np.ndarray, argument
132 gains: np.ndarray, argument
133 sens_max_analog: np.ndarray, argument
134 ) -> np.ndarray:
188 mean_img: np.ndarray, argument
189 var_img: np.ndarray, argument
192 ) -> Tuple[np.ndarray, np.ndarray]:
238 means: np.ndarray, argument
239 vars_: np.ndarray, argument
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| D | image_fov_utils.py | 243 isinstance(k, np.ndarray)):
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| D | image_processing_utils.py | 655 img = numpy.ndarray(
1085 img = numpy.ndarray(
1660 output_preview_img = numpy.ndarray.copy(numpy.flipud(input_preview_img))
1664 output_preview_img = numpy.ndarray.copy(numpy.fliplr(input_preview_img))
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| D | capture_read_noise_utils.py | 369 img = np.ndarray(
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| D | zoom_capture_utils.py | 178 img = numpy.ndarray.copy(img)
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| D | opencv_processing_utils.py | 1351 copy_img = numpy.ndarray.copy(img)
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