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Test3.py

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+def get_images_and_labels(path):
+    image_paths = [os.path.join(path, f) for f in os.listdir(path)]
+    # 新建连个list用于存放
+    face_samples = []
+    ids = []
+
+    # 遍历图片路径，导入图片和id添加到list中
+    for image_path in image_paths:
+
+        # 通过图片路径将其转换为灰度图片
+        img = Image.open(image_path).convert('L')
+
+        # 将图片转化为数组
+        img_np = np.array(img, 'uint8')
+
+        if os.path.split(image_path)[-1].split(".")[-1] != 'jpg':
+            continue
+
+        # 为了获取id，将图片和路径分裂并获取
+        id = int(os.path.split(image_path)[-1].split(".")[1])
+
+        # 调用熟悉的人脸分类器
+        detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+
+        faces = detector.detectMultiScale(img_np)
+
+        # 将获取的图片和id添加到list中
+        for (x, y, w, h) in faces:
+            face_samples.append(img_np[y:y + h, x:x + w])
+            ids.append(id)
+    return face_samples, ids