矫正扭曲和图片方向分类接口化

clas_api.py

@@ -0,0 +1,26 @@
+from flask import Flask, request
+from paddleclas import PaddleClas
+
+from util.common_util import process_request
+
+app = Flask(__name__)
+CLAS = PaddleClas(model_name="text_image_orientation")
+
+
+@app.route('/clas/orientation', methods=['POST'])
+@process_request
+def orientation():
+    """
+    判断图片旋转角度，逆时针旋转该角度后为正。可能值["0", "90", "180", "270"]
+    :return: 最有可能的两个角度
+    """
+    img_path = request.form.get('img_path')
+    clas_result = CLAS.predict(input_data=img_path)
+    clas_result = next(clas_result)[0]
+    if clas_result["scores"][0] < 0.5:
+        return ['0', '90']
+    return clas_result["label_names"]
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5002)

det_api.py

@@ -1,24 +1,23 @@
 import os.path
 
 import cv2
-from flask import Flask, request, Blueprint
+from flask import Flask, request
 
 from paddle_detection import detector
+from util import image_util
 from util.common_util import process_request
 
 app = Flask(__name__)
-det_bp = Blueprint('det_bp', __name__)
 
 
-@det_bp.route('/books', methods=['POST'])
+@app.route('/det/books', methods=['POST'])
 @process_request
 def books():
-    img_path = request.form['img_path']
+    img_path = request.form.get('img_path')
     image = cv2.imread(img_path)
     result = detector.get_book_areas(image)
 
-    dirname = os.path.dirname(img_path)
+    dirname, img_name, ext = image_util.parse_path(img_path)
-    img_name, ext = os.path.basename(img_path).rsplit('.', 1)
     books_path = []
     for i in range(len(result)):
         save_path = os.path.join(dirname, img_name + '_book_' + str(i) + '.' + ext)
@@ -27,7 +26,5 @@ def books():
     return books_path
 
 
-app.register_blueprint(det_bp, url_prefix='/det')
-
 if __name__ == '__main__':
     app.run('0.0.0.0', 5000)

dewarp_api.py

@@ -0,0 +1,26 @@
+import os
+
+import cv2
+from flask import Flask, request
+
+from doc_dewarp import dewarp
+from util import image_util
+from util.common_util import process_request
+
+app = Flask(__name__)
+
+
+@app.route('/dewarp', methods=['POST'])
+@process_request
+def dewarp():
+    img_path = request.form.get('img_path')
+    img = cv2.imread(img_path)
+    dewarped_img = dewarp.dewarp_image(img)
+    dirname, img_name, ext = image_util.parse_path(img_path)
+    save_path = os.path.join(dirname, img_name + '_dewarped.' + ext)
+    cv2.imwrite(save_path, dewarped_img)
+    return save_path
+
+
+if __name__ == '__main__':
+    app.run('0.0.0.0', 5001)

photo_review/auto_photo_review.py

@@ -182,15 +182,11 @@ def information_extraction(ie, phrecs, identity):
 
             result = merge_result(result, ie_result['result'])
         else:
-            target_images = []
+            target_images = model_util.request_book_areas(img_path)  # 识别文档区域并裁剪
-            target_images += model_util.request_book_areas(img_path)  # 识别文档区域并裁剪
-            if not target_images:
-                target_images.append(image)  # 识别失败
             angle_count = defaultdict(int, {'0': 0})  # 分割后图片的最优角度统计
             for target_image in target_images:
-                # dewarped_image = dewarp.dewarp_image(target_image)  # 去扭曲
+                dewarped_image = model_util.request_dewarped_image(target_image)  # 去扭曲
-                dewarped_image = target_image
+                angles = model_util.request_image_orientation(dewarped_image)
-                angles = image_util.parse_rotation_angles(dewarped_image)
 
                 split_results = image_util.split(dewarped_image)
                 for split_result in split_results:

util/image_util.py

@@ -283,3 +283,9 @@ def save_to_local(img_url, save_path=None):
         file.write(response.content)
 
     return save_path
+
+
+def parse_path(img_path):
+    dirname = os.path.dirname(img_path)
+    img_name, ext = os.path.basename(img_path).rsplit('.', 1)
+    return dirname, img_name, ext

util/model_util.py

@@ -1,6 +1,5 @@
 import logging
 
-import cv2
 import requests
 from tenacity import retry, stop_after_attempt, wait_random
 
@@ -8,13 +7,46 @@ from tenacity import retry, stop_after_attempt, wait_random
 @retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
        after=lambda x: logging.warning('获取文档区域失败！'))
 def request_book_areas(img_path):
+    """
+    请求文档区域识别接口
+    :param img_path: 待识别图片路径
+    :return: 文档图片路径列表
+    """
     url = 'http://det_api:5000/det/books'
     response = requests.post(url, {'img_path': img_path})
     if response.status_code == 200:
-        response_data = response.json()
+        return response.json()
-        books = []
-        for books_path in response_data:
-            books.append(cv2.imread(books_path))
-        return books
     else:
-        return []
+        return [img_path]
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('矫正扭曲图片失败！'))
+def request_dewarped_image(img_path):
+    """
+    请求矫正图片接口
+    :param img_path: 待矫正图片路径
+    :return: 矫正后的图片路径
+    """
+    url = 'http://det_api:5001/dewarp'
+    response = requests.post(url, {'img_path': img_path})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return img_path
+
+
+@retry(stop=stop_after_attempt(3), wait=wait_random(1, 3), reraise=True,
+       after=lambda x: logging.warning('获取图片方向失败！'))
+def request_image_orientation(img_path):
+    """
+    请求图片方向分类接口
+    :param img_path: 待分类图片路径
+    :return: 最有可能的两个图片方向
+    """
+    url = 'http://det_api:5002/clas/orientation'
+    response = requests.post(url, {'img_path': img_path})
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return ['0', '90']