优化图片的存储，及时删除处理过程中产生的图片

photo_mask/auto_photo_mask.py

@@ -54,11 +54,11 @@ def find_boxes(content, layout, offset=0, length=None, improve=False, image_path
     if improve:
         # 再次识别，提高精度
         image = cv2.imread(image_path)
-        img_name, img_ext = image_util.parse_save_path(image_path)
+        img_name, img_ext = common_util.parse_save_path(image_path)
         # 截图时偏大一点
         capture_box = common_util.zoom_rectangle(box, 0.2)
         captured_image = image_util.capture(image, capture_box)
-        captured_image_path = image_util.get_save_path(f'{img_name}.capture.{img_ext}')
+        captured_image_path = common_util.get_processed_img_path(f'{img_name}.capture.{img_ext}')
         cv2.imwrite(captured_image_path, captured_image)
         captured_a4_img_path, offset_x, offset_y = image_util.expand_to_a4_size(captured_image_path)
         try:
@@ -170,7 +170,7 @@ def handle_image_for_mask(split_result):
 def mask_photo(img_path, name, id_card_num, color=(255, 255, 255)):
     def _mask(ip, n, icn, c):
         i = cv2.imread(ip)
-        img_name, img_ext = image_util.parse_save_path(ip)
+        img_name, img_ext = common_util.parse_save_path(ip)
         do_mask = False
         split_results = image_util.split(ip)
         for split_result in split_results:
@@ -188,7 +188,7 @@ def mask_photo(img_path, name, id_card_num, color=(255, 255, 255)):
                     result[3] + y_offset,
                 )
                 cv2.rectangle(i, (int(result[0]), int(result[1])), (int(result[2]), int(result[3])), c, -1, 0)
-        masked_path = image_util.get_save_path(f'{img_name}.mask.{img_ext}')
+        masked_path = common_util.get_processed_img_path(f'{img_name}.mask.{img_ext}')
         cv2.imwrite(masked_path, i)
         return do_mask, masked_path
 
@@ -222,7 +222,7 @@ def photo_mask(pk_phhd, name, id_card_num):
         img_url = ufile.get_private_url(phrec.cfjaddress)
         if not img_url:
             continue
-        img_path = image_util.save_to_local(img_url)
+        img_path = common_util.save_to_local(img_url)
         is_masked, image = mask_photo(img_path, name, id_card_num)
 
         # 如果涂抹了要备份以及更新

photo_review/__init__.py

@@ -9,6 +9,8 @@ PHHD_BATCH_SIZE = 10
 SLEEP_MINUTES = 5
 # 是否发送报错邮件
 SEND_ERROR_EMAIL = True
+# 处理批号（这里仅起声明作用）
+BATCH_ID = ''
 
 '''
 别名配置
@@ -56,3 +58,9 @@ DISCHARGE_KEY = {
     '出院日期': ['出院日期', '出院时间'],
     '出院医嘱': ['出院医嘱']
 }
+
+
+def modify_batch_id(batch_id):
+    # 修改批号的接口
+    global BATCH_ID
+    BATCH_ID = batch_id

photo_review/auto_photo_review.py

@@ -1,6 +1,9 @@
 import json
 import logging
+import os
+import shutil
 import time
+import uuid
 from collections import defaultdict
 from time import sleep
 
@@ -16,7 +19,7 @@ from db import MysqlSession
 from db.mysql import BdYljg, BdYlks, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec, ZxIeReview, ZxIeResult
 from log import HOSTNAME
 from photo_review import PHHD_BATCH_SIZE, SLEEP_MINUTES, HOSPITAL_ALIAS, HOSPITAL_FILTER, DEPARTMENT_ALIAS, \
-    DEPARTMENT_FILTER, DISCHARGE_KEY
+    DEPARTMENT_FILTER, DISCHARGE_KEY, modify_batch_id, BATCH_ID
 from services.paddle_services import IE_KEY
 from ucloud import ufile
 from util import image_util, common_util, html_util, model_util
@@ -46,8 +49,8 @@ def get_better_image_from_qrcode(img_path, image_id, dpi=150):
             # 将渲染结果转换为OpenCV兼容的格式
             img = np.frombuffer(pix.samples, dtype=np.uint8).reshape((pix.height, pix.width, -1))
             img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
-            img_name, img_ext = image_util.parse_save_path(img_path)
+            img_name, img_ext = common_util.parse_save_path(img_path)
-            better_img_path = image_util.get_save_path(f'{img_name}.better.{img_ext}')
+            better_img_path = common_util.get_processed_img_path(f'{img_name}.better.{img_ext}')
             cv2.imwrite(better_img_path, img)
             return better_img_path, page.get_text()
         except Exception as ex:
@@ -100,20 +103,21 @@ def get_better_image_from_qrcode(img_path, image_id, dpi=150):
 
 
 # 关键信息提取
-def information_extraction(phrec, pk_phhd, identity):
+def information_extraction(phrec, pk_phhd):
     """
     处理单张图片
     :param phrec:图片信息
     :param pk_phhd:案子主键
-    :param identity:处理批次标识
     :return:记录类型，信息抽取结果
     """
-    img_path = image_util.get_img_path(phrec.cfjaddress)
+    original_img_path = common_util.get_img_path(phrec.cfjaddress)
-    if not img_path:
+    if not original_img_path:
         img_url = ufile.get_private_url(phrec.cfjaddress)
         if not img_url:
             return None, None, None
-        img_path = image_util.save_to_local(img_url)
+        original_img_path = common_util.save_to_local(img_url)
+    img_path = common_util.get_processed_img_path(phrec.cfjaddress)
+    shutil.copy2(original_img_path, img_path)
 
     # 尝试从二维码中获取高清图片
     better_img_path, text = get_better_image_from_qrcode(img_path, phrec.cfjaddress)
@@ -129,17 +133,26 @@ def information_extraction(phrec, pk_phhd, identity):
             )
         ocr_text = None  # 此处肯定不是出院记录，后续用不到
     else:
-        target_image = model_util.det_book(img_path)  # 识别文档区域并裁剪
+        if image_util.is_photo(img_path):
-        dewarped_image = model_util.dewarp(target_image)  # 去扭曲
+            book_img_path = model_util.det_book(img_path)  # 识别文档区域并裁剪
-        angles = model_util.clas_orientation(dewarped_image)
+            dewarped_img_path = model_util.dewarp(book_img_path)  # 去扭曲
-        rotated_img = image_util.rotate(dewarped_image, int(angles[0]))
+        else:  # todo:也可能是图片，后续添加细分逻辑
-        split_results = image_util.split(rotated_img)
+            dewarped_img_path = img_path
+        angles = model_util.clas_orientation(dewarped_img_path)
         ocr_result = []
-        for split_result in split_results:
+        rotated_img = None
-            if split_result['img'] is None:
+        for angle in angles:
-                continue
+            tmp_ocr_result = []
-            a4_img = image_util.expand_to_a4_size(split_result['img'])
+            tmp_rotated_img = image_util.rotate(dewarped_img_path, int(angle))
-            ocr_result += model_util.ocr(a4_img)
+            split_results = image_util.split(tmp_rotated_img)
+            for split_result in split_results:
+                if split_result['img'] is None:
+                    continue
+                a4_img = image_util.expand_to_a4_size(split_result['img'])
+                tmp_ocr_result += model_util.ocr(a4_img)
+            if len(tmp_ocr_result) > len(ocr_result):
+                ocr_result = tmp_ocr_result
+                rotated_img = tmp_rotated_img
         ocr_text = common_util.ocr_result_to_text(ocr_result)
         rec_type = model_util.clas_text(ocr_text) if ocr_text else None
         if rec_type == '基本医保结算单':
@@ -158,7 +171,7 @@ def information_extraction(phrec, pk_phhd, identity):
 
         now = common_util.get_default_datetime()
         session = MysqlSession()
-        session.add(ZxIeResult(pk_phhd=pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
+        session.add(ZxIeResult(pk_phhd=pk_phhd, pk_phrec=phrec.pk_phrec, id=BATCH_ID,
                                cfjaddress=phrec.cfjaddress, content=result_json, create_time=now,
                                creator=HOSTNAME, update_time=now, updater=HOSTNAME))
         session.commit()
@@ -175,23 +188,25 @@ def get_best_value_of_key(source, key):
     values = source.get(key)
     if values:
         for value in values:
-            text = value.get("text")
+            for v in value:
-            probability = value.get("probability")
+                text = v.get("text")
-            if text and probability > best_probability:
+                probability = v.get("probability")
-                result = text
+                if text and probability > best_probability:
-                best_probability = probability
+                    result = text
+                    best_probability = probability
     return result
 
 
 # 从keys中获取所有value组成list
 def get_values_of_key(source, key):
     result = []
-    value = source.get(key)
+    values = source.get(key)
-    if value:
+    if values:
-        for v in value:
+        for value in values:
-            v = v.get("text")
+            for v in value:
-            if v:
+                v = v.get("text")
-                result.append(v)
+                if v:
+                    result.append(v)
     # 去重
     return list(set(result))
 
@@ -424,10 +439,12 @@ def photo_review(pk_phhd, name):
     ).all()
     session.close()
     # 同一批图的标识
-    identity = int(time.time())
+    modify_batch_id(uuid.uuid4().hex)
     discharge_text = ''
     for phrec in phrecs:
-        rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd, identity)
+        processed_img_dir = common_util.get_processed_img_path('')
+        os.makedirs(processed_img_dir, exist_ok=True)
+        rec_type, ie_result, ocr_text = information_extraction(phrec, pk_phhd)
         if rec_type == '基本医保结算单':
             rec_result = settlement_result
         elif rec_type == '出院记录':
@@ -439,10 +456,11 @@ def photo_review(pk_phhd, name):
             rec_result = None
         if rec_result is not None:
             for key, value in ie_result.items():
-                if key == '页码':
+                rec_result[key].append(value)
-                    rec_result[key].append(value)  # 页码要区分来源，所以多包一层
+
-                else:
+        # 删除多余图片
-                    rec_result[key] += value
+        if os.path.exists(processed_img_dir) and os.path.isdir(processed_img_dir):
+            shutil.rmtree(processed_img_dir)
 
     settlement_data = settlement_task(pk_phhd, settlement_result)
     discharge_data = discharge_task(pk_phhd, discharge_result)

util/common_util.py

@@ -2,8 +2,12 @@ import logging
 import os
 from datetime import datetime
 
+import requests
 from opencc import OpenCC
+from tenacity import retry, stop_after_attempt, wait_random
 
+from log import PROJECT_ROOT
+from photo_review import BATCH_ID
 from util import string_util, model_util
 
 
@@ -255,3 +259,51 @@ def chinese_money_to_number(chinese_money_amount):
 def traditional_to_simple_chinese(traditional_chinese):
     converter = OpenCC('t2s')
     return converter.convert(traditional_chinese)
+
+
+def parse_img_url(url):
+    """
+    解析图片url
+    :param url: 图片url
+    :return: 图片名称和图片后缀
+    """
+    url = url.split('?')[0]
+    return os.path.basename(url)
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('保存图片失败！'))
+def save_to_local(img_url):
+    """
+    保存图片到本地
+    :param img_url: 图片url
+    :return: 本地保存地址
+    """
+    response = requests.get(img_url)
+    response.raise_for_status()  # 检查响应状态码是否正常
+
+    save_path = get_tmp_img_path(parse_img_url(img_url))
+    with open(save_path, 'wb') as file:
+        file.write(response.content)
+    return save_path
+
+
+def get_img_path(img_full_name):
+    save_path = get_tmp_img_path(img_full_name)
+    if os.path.exists(save_path):
+        return save_path
+    return None
+
+
+def get_tmp_img_path(img_full_name):
+    return os.path.join(PROJECT_ROOT, 'tmp_img', img_full_name)
+
+
+def get_processed_img_path(img_full_name):
+    return os.path.join(str(get_tmp_img_path(BATCH_ID)), img_full_name)
+
+
+def parse_save_path(img_path):
+    img_full_name = os.path.basename(img_path)
+    img_name, img_ext = img_full_name.rsplit('.', 1)
+    return img_name, img_ext

util/image_util.py

@@ -1,13 +1,10 @@
-import logging
 import math
-import os
 
 import cv2
 import numpy
-import requests
+from PIL import Image
-from tenacity import retry, stop_after_attempt, wait_random
 
-from log import PROJECT_ROOT
+from util import common_util
 
 
 def capture(image, rectangle):
@@ -42,14 +39,14 @@ def split(img_path, ratio=1.414, overlap=0.05, x_compensation=3):
     hw_ratio = height / width
     wh_ratio = width / height
 
-    img_name, img_ext = parse_save_path(img_path)
+    img_name, img_ext = common_util.parse_save_path(img_path)
     if hw_ratio > ratio:  # 纵向过长
         new_img_height = width * ratio
         step = width * (ratio - overlap)  # 偏移步长
         for i in range(math.ceil(height / step)):
             offset = round(step * i)
             cropped_img = capture(image, [0, offset, width, offset + new_img_height])
-            split_path = get_save_path(f'{img_name}.split_{i}.{img_ext}')
+            split_path = common_util.get_processed_img_path(f'{img_name}.split_{i}.{img_ext}')
             cv2.imwrite(split_path, cropped_img)
             split_result.append({'img': split_path, 'x_offset': 0, 'y_offset': offset})
     elif wh_ratio > ratio:  # 横向过长
@@ -58,7 +55,7 @@ def split(img_path, ratio=1.414, overlap=0.05, x_compensation=3):
         for i in range(math.ceil(width / step)):
             offset = round(step * i)
             cropped_img = capture(image, [offset, 0, offset + new_img_width, width])
-            split_path = get_save_path(f'{img_name}.split_{i}.{img_ext}')
+            split_path = common_util.get_processed_img_path(f'{img_name}.split_{i}.{img_ext}')
             cv2.imwrite(split_path, cropped_img)
             split_result.append({'img': split_path, 'x_offset': offset, 'y_offset': 0})
     else:
@@ -111,8 +108,8 @@ def rotate(img_path, angle):
     # 参数：原始图像 旋转参数 元素图像宽高
     rotated = cv2.warpAffine(image, matrix, (new_width, new_height))
 
-    img_name, img_ext = parse_save_path(img_path)
+    img_name, img_ext = common_util.parse_save_path(img_path)
-    rotated_path = get_save_path(f'{img_name}.rotate_{angle}.{img_ext}')
+    rotated_path = common_util.get_processed_img_path(f'{img_name}.rotate_{angle}.{img_ext}')
     cv2.imwrite(rotated_path, rotated)
     return rotated_path
 
@@ -178,7 +175,7 @@ def expand_to_a4_size(img_path):
     :return: 扩充后的图片NumPy数组和偏移量
     """
     image = cv2.imread(img_path)
-    img_name, img_ext = parse_save_path(img_path)
+    img_name, img_ext = common_util.parse_save_path(img_path)
     height, width = image.shape[:2]
     x_offset, y_offset = 0, 0
     hw_ratio = height / width
@@ -206,8 +203,9 @@ def expand_to_a4_size(img_path):
         exp_img = numpy.zeros((y_offset, width, 3), dtype='uint8')
         exp_img.fill(255)
         image = numpy.vstack([exp_img, image, exp_img])
-    # todo:未拓展时不要生成新的图片
+    else:
-    save_path = get_save_path(f'{img_name}.a4.{img_ext}')
+        return img_path, 0, 0
+    save_path = common_util.get_processed_img_path(f'{img_name}.a4.{img_ext}')
     cv2.imwrite(save_path, image)
     return save_path, x_offset, y_offset
 
@@ -240,45 +238,16 @@ def combined(img1, img2):
     return combined_img
 
 
-def parse_img_url(url):
+def is_photo(img_path):
     """
-    解析图片url
+    是否是拍照照片
-    :param url: 图片url
+    :param img_path: 图片路径
-    :return: 图片名称和图片后缀
+    :return: True:是照片；False:可能不是照片，也可能在传输过程中相机等信息丢失了
     """
-    url = url.split('?')[0]
+    img = Image.open(img_path)
-    return os.path.basename(url)
+    exif = img.getexif()
-
+    if exif:
-
+        # 271:相机制造商, 272:相机型号
-@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+        if any(tag in exif for tag in (271, 272)):
-       after=lambda x: logging.warning('保存图片失败！'))
+            return True
-def save_to_local(img_url):
+    return False
-    """
-    保存图片到本地
-    :param img_url: 图片url
-    :return: 本地保存地址
-    """
-    response = requests.get(img_url)
-    response.raise_for_status()  # 检查响应状态码是否正常
-
-    save_path = get_save_path(parse_img_url(img_url))
-    with open(save_path, 'wb') as file:
-        file.write(response.content)
-    return save_path
-
-
-def get_img_path(img_full_name):
-    save_path = get_save_path(img_full_name)
-    if os.path.exists(save_path):
-        return save_path
-    return None
-
-
-def get_save_path(img_full_name):
-    return os.path.join(PROJECT_ROOT, 'tmp_img', img_full_name)
-
-
-def parse_save_path(img_path):
-    img_full_name = os.path.basename(img_path)
-    img_name, img_ext = img_full_name.rsplit('.', 1)
-    return img_name, img_ext