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import numpy as np |
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import cv2 as cv |
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class DaSiamRPN: |
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def __init__(self, model_path, kernel_cls1_path, kernel_r1_path, backend_id=0, target_id=0): |
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self._model_path = model_path |
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self._kernel_cls1_path = kernel_cls1_path |
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self._kernel_r1_path = kernel_r1_path |
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self._backend_id = backend_id |
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self._target_id = target_id |
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self._param = cv.TrackerDaSiamRPN_Params() |
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self._param.model = self._model_path |
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self._param.kernel_cls1 = self._kernel_cls1_path |
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self._param.kernel_r1 = self._kernel_r1_path |
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self._param.backend = self._backend_id |
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self._param.target = self._target_id |
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self._model = cv.TrackerDaSiamRPN.create(self._param) |
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@property |
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def name(self): |
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return self.__class__.__name__ |
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def setBackend(self, backend_id): |
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self._backend_id = backend_id |
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self._param = cv.TrackerDaSiamRPN_Params() |
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self._param.model = self._model_path |
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self._param.kernel_cls1 = self._kernel_cls1_path |
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self._param.kernel_r1 = self._kernel_r1_path |
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self._param.backend = self._backend_id |
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self._param.target = self._target_id |
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self._model = cv.TrackerDaSiamRPN.create(self._param) |
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def setTarget(self, target_id): |
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self._target_id = target_id |
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self._param = cv.TrackerDaSiamRPN_Params() |
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self._param.model = self._model_path |
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self._param.kernel_cls1 = self._kernel_cls1_path |
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self._param.kernel_r1 = self._kernel_r1_path |
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self._param.backend = self._backend_id |
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self._param.target = self._target_id |
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self._model = cv.TrackerDaSiamRPN.create(self._param) |
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def init(self, image, roi): |
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self._model.init(image, roi) |
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def infer(self, image): |
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isLocated, bbox = self._model.update(image) |
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score = self._model.getTrackingScore() |
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return isLocated, bbox, score |