PaddleX/paddlex/inference/models/table_structure_recognition/result.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 copy
import cv2
import numpy as np
from pathlib import Path
import PIL
from PIL import Image, ImageDraw, ImageFont

from ...common.result import BaseCVResult, StrMixin, JsonMixin


class TableRecResult(BaseCVResult):
    """SaveTableResults"""

    def _get_input_fn(self):
        fn = super()._get_input_fn()
        if (page_idx := self["page_index"]) is not None:
            fp = Path(fn)
            stem, suffix = fp.stem, fp.suffix
            return f"{stem}_{page_idx}{suffix}"
        else:
            return fn

    def _to_img(self):
        image = self["input_img"]
        bbox_res = self["bbox"]
        if len(bbox_res) > 0 and len(bbox_res[0]) == 4:
            vis_img = self.draw_rectangle(image, bbox_res)
        else:
            vis_img = self.draw_bbox(image, bbox_res)
        return {"res": vis_img}

    def draw_rectangle(self, image, boxes):
        """draw_rectangle"""
        boxes = np.array(boxes)
        img_show = image.copy()
        for box in boxes.astype(int):
            x1, y1, x2, y2 = box
            cv2.rectangle(img_show, (x1, y1), (x2, y2), (255, 0, 0), 2)
        return img_show

    def draw_bbox(self, image, boxes):
        """draw_bbox"""
        for box in boxes:
            box = np.reshape(np.array(box), [-1, 1, 2]).astype(np.int64)
            image = cv2.polylines(np.array(image), [box], True, (255, 0, 0), 2)
        return image

    def _to_str(self, *args, **kwargs):
        data = copy.deepcopy(self)
        data.pop("input_img")
        return JsonMixin._to_str(data, *args, **kwargs)

    def _to_json(self, *args, **kwargs):
        data = copy.deepcopy(self)
        data.pop("input_img")
        return JsonMixin._to_json(data, *args, **kwargs)