添加涂抹功能，暂未完成上传云端功能

photo_mask.py

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+import logging
+import math
+import os
+import tempfile
+import traceback
+import urllib.request
+from time import sleep
+
+import cv2
+import numpy as np
+import paddleclas
+from paddleocr import PaddleOCR
+from sqlalchemy import update
+
+from auto_email.error_email import send_an_error_email
+from config.mysql import MysqlSession
+from config.photo_review import PHHD_BATCH_SIZE, SLEEP_MINUTES
+from models import ZxPhrec, ZxPhhd
+from ucloud import ucloud
+
+OCR = PaddleOCR(use_angle_cls=False, lang="ch", show_log=False, gpu_id=1)
+
+
+def open_image(img_path):
+    if img_path.startswith("http"):
+        # 发送HTTP请求并获取图像数据
+        resp = urllib.request.urlopen(img_path)
+        # 将数据读取为字节流
+        image_data = resp.read()
+        # 将字节流转换为NumPy数组
+        image_np = np.frombuffer(image_data, np.uint8)
+        # 解码NumPy数组为OpenCV图像格式
+        image = cv2.imdecode(image_np, cv2.IMREAD_COLOR)
+    else:
+        image = cv2.imread(img_path)
+    return image
+
+
+def split_image(img, max_ratio=2.82, best_ration=1.41, overlap=0.05):
+    split_result = []
+    # 获取图片的宽度和高度
+    height, width = img.shape[:2]
+    # 计算宽高比
+    ratio = max(width, height) / min(width, height)
+    # 检查是否需要裁剪
+    if ratio > max_ratio:
+        # 确定裁剪的尺寸，保持长宽比，以较短边为基准
+        new_ratio = best_ration - overlap
+        if width < height:
+            # 高度是较长边
+            cropped_width = width * best_ration
+            for i in range(math.ceil(height / (width * new_ratio))):
+                offset = round(width * new_ratio * i)
+                # 参数形式为[y1:y2, x1:x2]
+                cropped_img = img[offset:round(offset + cropped_width), 0:width]
+                split_result.append({"img": cropped_img, "x_offset": 0, "y_offset": offset})
+            # 最后一次裁剪时不足的部分填充黑色
+            last_img = split_result[-1]["img"]
+            split_result[-1]["img"] = cv2.copyMakeBorder(last_img, 0, round(cropped_width - last_img.shape[0]), 0, 0,
+                                                         cv2.BORDER_CONSTANT, value=(0, 0, 0))
+        else:
+            # 宽度是较长边
+            cropped_height = height * best_ration
+            for i in range(math.ceil(width / (height * new_ratio))):
+                offset = round(height * new_ratio * i)
+                cropped_img = img[0:height, offset:round(offset + cropped_height)]
+                split_result.append({"img": cropped_img, "x_offset": offset, "y_offset": 0})
+            # 最后一次裁剪时不足的部分填充黑色
+            last_img = split_result[-1]["img"]
+            split_result[-1]["img"] = cv2.copyMakeBorder(last_img, 0, 0, 0, round(cropped_height - last_img.shape[1]),
+                                                         cv2.BORDER_CONSTANT, value=(0, 0, 0))
+    else:
+        split_result.append({"img": img, "x_offset": 0, "y_offset": 0})
+    return split_result
+
+
+# 获取图片旋转角度
+def get_image_rotation_angles(img):
+    angles = ['0', '90']
+    model = paddleclas.PaddleClas(model_name="text_image_orientation")
+    result = model.predict(input_data=img)
+    try:
+        result = next(result)[0]
+        if result["scores"][0] < 0.5:
+            return angles
+        angles = result["label_names"]
+    except Exception as e:
+        logging.error("获取图片旋转角度失败", exc_info=e)
+    return angles
+
+
+def rotate_image(img, angle):
+    if angle == 0:
+        return img
+    height, width, _ = img.shape
+    if angle == 180:
+        new_width = width
+        new_height = height
+    else:
+        new_width = height
+        new_height = width
+    # 绕图像的中心旋转
+    # 参数：旋转中心 旋转度数 scale
+    matrix = cv2.getRotationMatrix2D((width / 2, height / 2), angle, 1)
+    # 旋转后平移
+    matrix[0, 2] += (new_width - width) / 2
+    matrix[1, 2] += (new_height - height) / 2
+    # 参数：原始图像 旋转参数 元素图像宽高
+    rotated = cv2.warpAffine(img, matrix, (new_width, new_height))
+    return rotated
+
+
+def rotate_rectangle(rectangle, center, angle):
+    def rotate_point(pt, angle, center):
+        matrix = cv2.getRotationMatrix2D(center, angle, 1)
+        # 旋转后平移
+        matrix[0, 2] += center[1] - center[0]
+        matrix[1, 2] += center[0] - center[1]
+
+        reverse_matrix = cv2.invertAffineTransform(matrix)
+
+        pt = np.array([[pt[0]], [pt[1]], [1]])
+        return np.dot(reverse_matrix, pt)
+
+    x1, y1, x2, y2 = rectangle
+
+    # 计算矩形的四个顶点
+    top_left = (x1, y1)
+    bot_left = (x1, y2)
+    top_right = (x2, y1)
+    bot_right = (x2, y2)
+
+    # 旋转矩形的四个顶点
+    rot_top_left = rotate_point(top_left, angle, center).astype(int)
+    rot_bot_left = rotate_point(bot_left, angle, center).astype(int)
+    rot_bot_right = rotate_point(bot_right, angle, center).astype(int)
+    rot_top_right = rotate_point(top_right, angle, center).astype(int)
+
+    # 找出旋转后矩形的新左上角和右下角坐标
+    new_top_left = (min(rot_top_left[0], rot_bot_left[0], rot_bot_right[0], rot_top_right[0]),
+                    min(rot_top_left[1], rot_bot_left[1], rot_bot_right[1], rot_top_right[1]))
+    new_bot_right = (max(rot_top_left[0], rot_bot_left[0], rot_bot_right[0], rot_top_right[0]),
+                     max(rot_top_left[1], rot_bot_left[1], rot_bot_right[1], rot_top_right[1]))
+
+    return [new_top_left[0], new_top_left[1], new_bot_right[0], new_bot_right[1]]
+
+
+def get_ocr_layout(ocr, img_path):
+    def _get_box(old_box):
+        new_box = [
+            min(old_box[0][0], old_box[3][0]),  # x1
+            min(old_box[0][1], old_box[1][1]),  # y1
+            max(old_box[1][0], old_box[2][0]),  # x2
+            max(old_box[2][1], old_box[3][1]),  # y2
+        ]
+        return new_box
+
+    def _normal_box(box_data):
+        # Ensure the height and width of bbox are greater than zero
+        if box_data[3] - box_data[1] < 0 or box_data[2] - box_data[0] < 0:
+            return False
+        return True
+
+    layout = []
+    ocr_result = ocr.ocr(img_path, cls=False)
+    ocr_result = ocr_result[0]
+    if not ocr_result:
+        return layout
+    for segment in ocr_result:
+        box = segment[0]
+        box = _get_box(box)
+        if not _normal_box(box):
+            continue
+        text = segment[1][0]
+        layout.append((box, text))
+    return layout
+
+
+def find_box_of_content(content, layout):
+    full_box = layout[0]
+    box_len = full_box[2] - full_box[0]
+    text = layout[1]
+    text_len = len(text)
+    char_len = box_len / text_len
+    index = text.index(content)
+    return (
+        full_box[0] + index * char_len,
+        full_box[1],
+        full_box[0] + (index + len(content)) * char_len,
+        full_box[3],
+    )
+
+
+def mask_image(image, content):
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+        cv2.imwrite(temp_file.name, image)
+
+    result = []
+    try:
+        layouts = get_ocr_layout(OCR, temp_file.name)
+        if not layouts:
+            # 无识别结果
+            return result
+        else:
+            # 涂抹
+            for layout in layouts:
+                if content in layout[1]:
+                    result.append(find_box_of_content(content, layout))
+            return result
+    except Exception as e:
+        logging.error("涂抹时出错", exc_info=e)
+    finally:
+        try:
+            os.remove(temp_file.name)
+        except Exception as e:
+            logging.info(f"删除临时文件 {temp_file.name} 时出错", exc_info=e)
+
+
+def photo_mask(pk_phhd, content):
+    session = MysqlSession()
+    phrecs = session.query(ZxPhrec.pk_phrec, ZxPhrec.pk_phhd, ZxPhrec.cfjaddress) \
+        .filter(ZxPhrec.pk_phhd == pk_phhd) \
+        .filter(ZxPhrec.cRectype.in_(["3", "4"])) \
+        .all()
+    session.close()
+    for phrec in phrecs:
+        img_url = ucloud.get_private_url(phrec.cfjaddress)
+        if not img_url:
+            continue
+        # 打开图片
+        image = open_image(img_url)
+        split_result = split_image(image)
+        for img in split_result:
+            angles = get_image_rotation_angles(img["img"])
+            rotated_img = rotate_image(img["img"], int(angles[0]))
+            results = mask_image(rotated_img, content)
+
+            for result in results:
+                height, width = img["img"].shape[:2]
+                center = (width / 2, height / 2)
+                result = rotate_rectangle(result, center, int(angles[0]))
+                result = (
+                    result[0] + img["x_offset"],
+                    result[1] + img["y_offset"],
+                    result[2] + img["x_offset"],
+                    result[3] + img["y_offset"],
+                )
+                cv2.rectangle(image, (int(result[0]), int(result[1])), (int(result[2]), int(result[3])),
+                              (255, 255, 255), -1, 0)
+        cv2.imwrite(f"./mask_test/{phrec.cfjaddress}.jpg", image)
+
+
+if __name__ == '__main__':
+    try:
+        while 1:
+            session = MysqlSession()
+            phhds = session.query(ZxPhhd.pk_phhd, ZxPhhd.cXm).filter(
+                ZxPhhd.paint_flag == "1"
+            ).limit(PHHD_BATCH_SIZE).all()
+            # 将状态改为正在涂抹中
+            pk_phhd_values = [phhd.pk_phhd for phhd in phhds]
+            update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd.in_(pk_phhd_values)).values(paint_flag="2"))
+            session.execute(update_flag)
+            session.commit()
+            session.close()
+            if phhds:
+                for phhd in phhds:
+                    pk_phhd = phhd.pk_phhd
+                    logging.info(f"开始涂抹：{pk_phhd}")
+                    photo_mask(pk_phhd, phhd.cXm)
+
+                    # 识别完成更新标识
+                    session = MysqlSession()
+                    update_flag = (update(ZxPhhd).where(ZxPhhd.pk_phhd == pk_phhd).values(paint_flag="8"))
+                    session.execute(update_flag)
+                    session.commit()
+                    session.close()
+            else:
+                # 没有查询到新案子，等待一段时间后再查
+                log = logging.getLogger()
+                log.info(f"暂未查询到需要涂抹的案子，等待{SLEEP_MINUTES}分钟...")
+                sleep(SLEEP_MINUTES * 60)
+    except Exception as e:
+        logging.error(traceback.format_exc())
+        send_an_error_email(program_name='照片涂抹脚本', error_name=repr(e), error_detail=traceback.format_exc())