diff --git a/src/face3d/extract_kp_videos_safe.py b/src/face3d/extract_kp_videos_safe.py
index 5141ba3a..dafaedca 100644
--- a/src/face3d/extract_kp_videos_safe.py
+++ b/src/face3d/extract_kp_videos_safe.py
@@ -71,7 +71,10 @@ def extract_keypoint(self, images, name=None, info=True):
                         # face detection -> face alignment.
                         img = np.array(images)
                         bboxes = self.det_net.detect_faces(images, 0.97)
-                        
+                        if len(bboxes) == 0:
+                            bboxes = self.det_net.detect_faces(images, 0.5)
+                        if len(bboxes) == 0:
+                            bboxes = self.det_net.detect_faces(images, 0.2)
                         bboxes = bboxes[0]
                         img = img[int(bboxes[1]):int(bboxes[3]), int(bboxes[0]):int(bboxes[2]), :]
 
diff --git a/src/face3d/util/my_awing_arch.py b/src/face3d/util/my_awing_arch.py
index cd565617..308752f6 100644
--- a/src/face3d/util/my_awing_arch.py
+++ b/src/face3d/util/my_awing_arch.py
@@ -15,7 +15,7 @@ def calculate_points(heatmaps):
     indexes = np.argmax(heatline, axis=2)
 
     preds = np.stack((indexes % W, indexes // W), axis=2)
-    preds = preds.astype(np.float, copy=False)
+    preds = preds.astype(float, copy=False)
 
     inr = indexes.ravel()
 
diff --git a/src/face3d/util/preprocess.py b/src/face3d/util/preprocess.py
index b77a3a40..cf002ea8 100644
--- a/src/face3d/util/preprocess.py
+++ b/src/face3d/util/preprocess.py
@@ -9,7 +9,10 @@
 from skimage import transform as trans
 import torch
 import warnings
-warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning) 
+try:
+    warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)
+except AttributeError:
+    pass  # numpy 2.x removed VisibleDeprecationWarning
 warnings.filterwarnings("ignore", category=FutureWarning) 
 
 
@@ -43,9 +46,9 @@ def resize_n_crop_img(img, lm, t, s, target_size=224., mask=None):
     w0, h0 = img.size
     w = (w0*s).astype(np.int32)
     h = (h0*s).astype(np.int32)
-    left = (w/2 - target_size/2 + float((t[0] - w0/2)*s)).astype(np.int32)
+    left = (w/2 - target_size/2 + np.array((t[0] - w0/2)*s).item()).astype(np.int32)
     right = left + target_size
-    up = (h/2 - target_size/2 + float((h0/2 - t[1])*s)).astype(np.int32)
+    up = (h/2 - target_size/2 + np.array((h0/2 - t[1])*s).item()).astype(np.int32)
     below = up + target_size
 
     img = img.resize((w, h), resample=Image.BICUBIC)
@@ -98,6 +101,6 @@ def align_img(img, lm, lm3D, mask=None, target_size=224., rescale_factor=102.):
 
     # processing the image
     img_new, lm_new, mask_new = resize_n_crop_img(img, lm, t, s, target_size=target_size, mask=mask)
-    trans_params = np.array([w0, h0, s, t[0], t[1]])
+    trans_params = np.array([w0, h0, float(s), float(np.array(t[0]).flat[0]), float(np.array(t[1]).flat[0])])
 
     return trans_params, img_new, lm_new, mask_new