diff --git a/src/eynollah/eynollah.py b/src/eynollah/eynollah.py
index 0cad343..4823559 100644
--- a/src/eynollah/eynollah.py
+++ b/src/eynollah/eynollah.py
@@ -327,7 +327,7 @@ class Eynollah:
                               page_coord[2]: page_coord[3]]
             img_in = np.repeat(img_1ch[:, :, np.newaxis], 3, axis=2)
         img_in = img_in / 255.0
-        img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST)
+        img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST).astype(np.float16)
 
         label_p_pred = self.model_zoo.get("col_classifier").predict(img_in[np.newaxis], verbose=0)[0]
         num_col = np.argmax(label_p_pred) + 1
@@ -386,7 +386,7 @@ class Eynollah:
                                   image['coord_page'][2]: image['coord_page'][3]]
                 img_in = np.repeat(img_1ch[:, :, np.newaxis], 3, axis=2)
             img_in = img_in / 255.0
-            img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST)
+            img_in = cv2.resize(img_in, (448, 448), interpolation=cv2.INTER_NEAREST).astype(np.float16)
 
             label_p_pred = self.model_zoo.get("col_classifier").predict(img_in[np.newaxis], verbose=0)[0]
             num_col = np.argmax(label_p_pred) + 1
@@ -895,7 +895,7 @@ class Eynollah:
         return cropped_page, page_coord
 
     def extract_text_regions_new(self, img, patches, cols):
-        self.logger.debug("enter extract_text_regions")
+        self.logger.debug("enter extract_text_regions_new")
         img_height_h = img.shape[0]
         img_width_h = img.shape[1]
 
@@ -927,10 +927,9 @@ class Eynollah:
         else:
             prediction_regions = self.do_prediction(
                 False, img, self.model_zoo.get("region_fl_np"),
-                n_batch_inference=2,
                 thresholding_for_heading=False)
         prediction_regions = resize_image(prediction_regions, img_height_h, img_width_h)
-        self.logger.debug("exit extract_text_regions")
+        self.logger.debug("exit extract_text_regions_new")
         return prediction_regions
 
     def extract_text_regions(self, img, patches, cols):