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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- import os
- import numpy as np
- from ....utils import logging
- from ..base import BaseComponent
- from .det import restructured_boxes
- def extract_masks_from_boxes(boxes, masks):
- """
- Extracts the portion of each mask that is within the corresponding box.
- """
- new_masks = []
- for i, box in enumerate(boxes):
- x_min, y_min, x_max, y_max = box["coordinate"]
- x_min, y_min, x_max, y_max = map(
- lambda x: int(round(x)), [x_min, y_min, x_max, y_max]
- )
- cropped_mask = masks[i][y_min:y_max, x_min:x_max]
- new_masks.append(cropped_mask)
- return new_masks
- class InstanceSegPostProcess(BaseComponent):
- """Save Result Transform"""
- INPUT_KEYS = ["boxes", "masks"]
- OUTPUT_KEYS = ["img_path", "boxes", "masks"]
- DEAULT_INPUTS = {"boxes": "boxes", "masks": "masks"}
- DEAULT_OUTPUTS = {
- "boxes": "boxes",
- "masks": "masks",
- }
- def __init__(self, threshold=0.5, labels=None):
- super().__init__()
- self.threshold = threshold
- self.labels = labels
- def apply(self, boxes, masks):
- """apply"""
- expect_boxes = (boxes[:, 1] > self.threshold) & (boxes[:, 0] > -1)
- boxes = boxes[expect_boxes, :]
- boxes = restructured_boxes(boxes, self.labels)
- masks = masks[expect_boxes, :, :]
- masks = extract_masks_from_boxes(boxes, masks)
- result = {"boxes": boxes, "masks": masks}
- return result
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