diff --git a/deploy/pipeline/pipeline.py b/deploy/pipeline/pipeline.py
index e13afeb0a28aee77ca2ad190b17dee19dea0d478..54bbc78e5a85858073e0adadd4976cbf6a93eaa2 100644
--- a/deploy/pipeline/pipeline.py
+++ b/deploy/pipeline/pipeline.py
@@ -495,6 +495,7 @@ class PipePredictor(object):
         # det -> attr
         batch_loop_cnt = math.ceil(
             float(len(input)) / self.det_predictor.batch_size)
+        self.warmup_frame = min(10, len(input)//2) - 1
         for i in range(batch_loop_cnt):
             start_index = i * self.det_predictor.batch_size
             end_index = min((i + 1) * self.det_predictor.batch_size, len(input))
diff --git a/deploy/python/visualize.py b/deploy/python/visualize.py
index 4bc2e17832bcfc7450e7c1704bb8064824734565..120b85d1614dfefd4cc1d26330c4d5b4dce00906 100644
--- a/deploy/python/visualize.py
+++ b/deploy/python/visualize.py
@@ -378,7 +378,7 @@ def visualize_action(im,
     im = cv2.imread(im) if isinstance(im, str) else im
     im_h, im_w = im.shape[:2]
 
-    text_scale = max(1, im.shape[1] / 1600.)
+    text_scale = max(1, im.shape[1] / 400.)
     text_thickness = 2
 
     if action_visual_collector:
@@ -418,7 +418,7 @@ def visualize_vehicleplate(im, results, boxes=None):
         im = np.ascontiguousarray(np.copy(im))
 
     im_h, im_w = im.shape[:2]
-    text_scale = max(1.0, im.shape[0] / 1600.)
+    text_scale = max(1.0, im.shape[0] / 400.)
     text_thickness = 2
 
     line_inter = im.shape[0] / 40.