PaddleX/paddlex/inference/results/seg.py

# 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 numpy as np
import PIL
from PIL import Image
import copy
import json

from ...utils import logging
from .base import BaseResult


class SegResult(BaseResult):
    """Save Result Transform"""

    def __init__(self, data):
        super().__init__(data)
        self.data = data
        # We use pillow backend to save both numpy arrays and PIL Image objects
        self._img_writer.set_backend("pillow", format_="PNG")

    def _get_res_img(self):
        """apply"""
        seg_map = self.data["pred"]
        pc_map = self.get_pseudo_color_map(seg_map[0])
        return pc_map

    def get_pseudo_color_map(self, pred):
        """get_pseudo_color_map"""
        if pred.min() < 0 or pred.max() > 255:
            raise ValueError("`pred` cannot be cast to uint8.")
        pred = pred.astype(np.uint8)
        pred_mask = Image.fromarray(pred, mode="P")
        color_map = self._get_color_map_list(256)
        pred_mask.putpalette(color_map)
        return pred_mask

    @staticmethod
    def _get_color_map_list(num_classes, custom_color=None):
        """_get_color_map_list"""
        num_classes += 1
        color_map = num_classes * [0, 0, 0]
        for i in range(0, num_classes):
            j = 0
            lab = i
            while lab:
                color_map[i * 3] |= ((lab >> 0) & 1) << (7 - j)
                color_map[i * 3 + 1] |= ((lab >> 1) & 1) << (7 - j)
                color_map[i * 3 + 2] |= ((lab >> 2) & 1) << (7 - j)
                j += 1
                lab >>= 3
        color_map = color_map[3:]

        if custom_color:
            color_map[: len(custom_color)] = custom_color
        return color_map

    def print(self, json_format=True, indent=4, ensure_ascii=False):
        str_ = copy.deepcopy(self)
        del str_["pred"]
        if json_format:
            str_ = json.dumps(str_, indent=indent, ensure_ascii=ensure_ascii)
        logging.info(str_)