优化图片的存储，及时删除处理过程中产生的图片

util/image_util.py

@@ -1,13 +1,10 @@
-import logging
 import math
-import os
 
 import cv2
 import numpy
-import requests
-from tenacity import retry, stop_after_attempt, wait_random
+from PIL import Image
 
-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)
-    rotated_path = get_save_path(f'{img_name}.rotate_{angle}.{img_ext}')
+    img_name, img_ext = common_util.parse_save_path(img_path)
+    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
-    save_path = get_save_path(f'{img_name}.a4.{img_ext}')
+    else:
+        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
-    :param url: 图片url
-    :return: 图片名称和图片后缀
+    是否是拍照照片
+    :param img_path: 图片路径
+    :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]
-    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_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
+    img = Image.open(img_path)
+    exif = img.getexif()
+    if exif:
+        # 271:相机制造商, 272:相机型号
+        if any(tag in exif for tag in (271, 272)):
+            return True
+    return False