adjust print statements and close figures

gradio_demo/barc_demo_v6.py

@@ -21,6 +21,7 @@ import cv2
 from matplotlib import pyplot as plt
 from PIL import Image
 import random
+from datetime import datetime
 import gradio as gr
 
 import sys
@@ -120,6 +121,7 @@ def run_bbox_inference(input_image):
     img, bbox = detect_object(model=model_bbox, img_path_or_img=input_image, confidence=0.5)
     fig = plt.figure()   #  plt.figure(figsize=(20,30))
     plt.imsave(out_path, img)
+    plt.close()
     return img, bbox
 # -------------------------------------------------------------------------------------------------------------------- #
 
@@ -195,9 +197,11 @@ def run_barc_inference(input_image, bbox=None):
 total_count = 0
 
 def run_complete_inference(img_path_or_img, crop_choice):
+    now = datetime.now()
+    dt_string = now.strftime("%d/%m/%Y %H:%M:%S")
     global total_count
     total_count += 1
-    print('total count: ' + str(total_count))
+    print(dt_string + ' total count: ' + str(total_count))
     # depending on crop_choice: run faster r-cnn or take the input image directly
     if crop_choice == "input image is cropped":
         if isinstance(img_path_or_img, str):

src/stacked_hourglass/datasets/imgcropslist.py

@@ -29,7 +29,7 @@ class ImgCrops(data.Dataset):
         self.test_name_list = []
         for ind in np.arange(0, len(self.image_list)):
             self.test_name_list.append(str(ind))
-        print('len(dataset): ' + str(self.__len__()))
+        # print('len(dataset): ' + str(self.__len__()))
 
     def __getitem__(self, index):
         '''img_name = self.test_name_list[index]