xznsh项目中巡检机制调研代码及文档

paddlehub_dec_face/paddlehub_dec_face_demo.py

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+import os 
+import paddlehub as hub
+import cv2
+
+def draw_img(x,y,w,h,img,save_path):
+    # # 判断人脸矩形宽高比是否为正脸
+    if w / h < 1.2 and w / h > 0.8:  
+        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)  
+        label = 'Frontal Face'
+    else:  
+        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), 2)  
+        label = 'Not Frontal'
+    # 在图片上打标签    
+    cv2.putText(img, label, (x, y - 5),cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 255), 2)
+    # cv2.imwrite(save_path, img)
+
+# 文件夹路径
+dir_path = '/home/dusr/data/xznsh/img/'  
+
+# 文件保存路径
+save_dir = '/home/dusr/data/xznsh/img_result'
+
+# 获取folder_path下的所有文件
+files = os.listdir(dir_path)  
+# 遍历所有文件
+for file in files:
+    # 获取文件路径
+    file_path = os.path.join(dir_path, file) 
+    save_path = os.path.join(save_dir, "result_"+file)
+    img = cv2.imread(file_path)
+    # 判断是否为图片文件
+    if file_path.endswith('.jpg') or file_path.endswith('.png'):
+
+        # face_detector = hub.Module(name="pyramidbox_lite_server")
+        face_detector = hub.Module(name="pyramidbox_face_detection")
+        file_path = r'/home/dusr/data/xznsh/img/frame_1640.jpg'
+        # result = face_detector.face_detection(images=[cv2.imread(file_path)])
+        # result = face_detector.face_detection(paths=[file_path])
+        result = face_detector.face_detection(paths=[file_path])
+        print(file_path)
+        print(result)
+        # 获取图片路径 path的值
+        path = result[0]['path']  
+        # 获取data的值
+        data = result[0]['data']
+        if data != []:
+            # 获取人脸置信度confidence的值
+            confidence = data[0]['confidence']
+
+            # 获取人脸左上角x坐标 left的值
+            lx = data[0]['left']  
+
+            # 获取人脸左上角y坐标 top的值
+            ly = data[0]['top']
+
+            # 获取人脸右下角x坐标 right的值 
+            rx = data[0]['right']  
+
+            # 获取人脸右下角y坐标 bottom的值
+            ry = data[0]['bottom']
+            w = rx -lx
+            h = ry-ly
+            x = lx
+            y = ly
+
+            draw_img(x,y,w,h,img,save_path)
+        else:
+            cv2.imwrite(save_path, img)
+            print("No facial information was detected")