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@@ -19,12 +19,14 @@ class Detector(object):
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config = munchify(configuration)
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self.img_proc = Pipeline()
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- self.img_proc.rescale(
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- min_size=config.preprocess.min_size,
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- min_scale=config.preprocess.scale)
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-
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self.img_proc.find_border()
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+ if config.preprocess.min_size:
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+ self.img_proc.rescale(
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+ min_size=config.preprocess.min_size,
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+ min_scale=config.preprocess.scale)
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+
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+
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self.img_proc.preprocess(
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equalize=False, sigma=config.preprocess.sigma)
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@@ -32,7 +34,6 @@ class Detector(object):
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type=BinarizerType.gauss_local,
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use_masked=True,
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use_cv2=True,
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- sigma=5.0,
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window_size=config.threshold.window_size,
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offset=2.0,
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)
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@@ -44,7 +45,7 @@ class Detector(object):
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iterations=config.postprocess.dilate_iterations)
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self.bbox_proc = Pipeline()
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- self.bbox_proc.detect()
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+ self.bbox_proc.detect(use_masked=True)
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_, splitter = self.bbox_proc.split_bboxes(
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preproc=Pipeline(), detector=Pipeline())
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_, bbox_filter = self.bbox_proc.bbox_filter(
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@@ -52,17 +53,17 @@ class Detector(object):
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nms_threshold=0.3,
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enlarge=0.01,
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)
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- _, scorer = self.bbox_proc.score()
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+ # _, scorer = self.bbox_proc.score()
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self.img_proc.requires_input(splitter.set_image)
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self.img_proc.requires_input(bbox_filter.set_image)
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- self.img_proc.requires_input(scorer.set_image)
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+ # self.img_proc.requires_input(scorer.set_image)
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def __call__(self, im: np.ndarray) -> T.List[BBox]:
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_im = self.img_proc(im)
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- bboxes, labels, scores = self.bbox_proc(_im)
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+ det_result = self.bbox_proc(_im)
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- return bboxes
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+ return det_result.bboxes
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