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@@ -20,7 +20,7 @@ def predict_img(
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return PaddleYoloDetector.predict(
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return PaddleYoloDetector.predict(
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img,
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img,
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- conf_threshold=0.3,
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+ conf_threshold=0.1,
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overlaps_iou_threshold=0.85,
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overlaps_iou_threshold=0.85,
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overlaps_max_count=3,
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overlaps_max_count=3,
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**kwargs,
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**kwargs,
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@@ -36,11 +36,13 @@ class LayoutBox:
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clazz_name: Optional[str],
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clazz_name: Optional[str],
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bbox: List[int],
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bbox: List[int],
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conf: float,
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conf: float,
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+ full_img: Optional[np.ndarray]=None,
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):
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):
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self.clazz = clazz
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self.clazz = clazz
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self.clazz_name = clazz_name
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self.clazz_name = clazz_name
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self.bbox = bbox
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self.bbox = bbox
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self.conf = conf
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self.conf = conf
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+ self.full_img = full_img
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@property
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@property
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def ltrb(self):
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def ltrb(self):
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@@ -84,10 +86,15 @@ class LayoutBox:
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"""
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"""
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返回中间服务所需的格式
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返回中间服务所需的格式
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"""
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"""
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+ if isinstance(self.full_img, np.ndarray):
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+ h, w = self.full_img.shape[:2]
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+ bbox = self.clip_bbox(self.bbox, h, w)
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+ else:
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+ bbox = self.ltrb
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return {
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return {
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"class": self.clazz,
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"class": self.clazz,
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"class_name": self.clazz_name,
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"class_name": self.clazz_name,
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- "bbox": self.ltrb,
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+ "bbox": bbox,
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"confidence": self.conf,
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"confidence": self.conf,
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}
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}
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@@ -100,5 +107,17 @@ class LayoutBox:
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conf=d["confidence"],
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conf=d["confidence"],
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)
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)
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+ @staticmethod
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+ def clip_bbox(bbox: List[int], img_h: int, img_w: int) -> List[int]:
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+ """
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+ 裁剪 bbox 尺寸以防止超出图像边界。
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+ """
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+ l, t, r, b = bbox
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+ l = max(0, int(l))
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+ t = max(0, int(t))
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+ r = min(img_w, int(r))
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+ b = min(img_h, int(b))
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+ return [l, t, r, b]
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+
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def __repr__(self):
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def __repr__(self):
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return f"LayoutBox(class={self.clazz}, class_name={self.clazz_name}, bbox={self.bbox}, conf={self.conf})"
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return f"LayoutBox(class={self.clazz}, class_name={self.clazz_name}, bbox={self.bbox}, conf={self.conf})"
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