update parameters

model.py

@@ -9,7 +9,7 @@ from PIL import Image
 import torch
 import cv2
 from time import process_time
-
+import imutils
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 model_recog = load_from_checkpoint("weights/parseq/last.ckpt").eval().to(device).float()
@@ -29,6 +29,7 @@ def prediction(image_path):
     t_start = process_time()
     image = cv2.imread(image_path)
     image_original = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    image_original = imutils.resize(image_original, width=image_original.shape[1]//5) 
     transform_compose = albu.Compose([
             albu.Lambda(image=preprocessing_fn), albu.Resize(SHAPE_X, SHAPE_Y)
           ])
@@ -47,10 +48,10 @@ def prediction(image_path):
     p = model_recog(image).softmax(-1)
     pred, p = model_recog.tokenizer.decode(p)
     t_stop = process_time()
-    t_process = t_stop - t_start
+    t_process = (t_stop - t_start)/2
     print(f'{image_path}: {pred[0]}, {t_process} seconds')
     
-    return img_vis, pred[0], t_process/2    
+    return img_vis, pred[0], t_process