removed logging

app.py

@@ -18,22 +18,7 @@ from PIL import Image
 from IPython.display import display
 import io
 import pathlib
-import logging
 
-# Create a logging instance
-logger = logging.getLogger('my_application')
-logger.setLevel(logging.INFO) # you can set this to be DEBUG, INFO, ERROR
-
-# Assign a file-handler to that instance
-fh = logging.FileHandler("error.txt")
-fh.setLevel(logging.INFO) # again, you can set this differently
-
-# Format your logs (optional)
-formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-fh.setFormatter(formatter) # This will set the format to the file handler
-
-# Add the handler to your logging instance
-logger.addHandler(fh)
 
 RoboflowAPI = os.environ['RoboflowAPI']
 RoboflowCocoAPI = os.environ['RoboflowCocoAPI']
@@ -408,35 +393,32 @@ def show_context_rcnn_inference(
 
 
 def segment(image):
-    try:
-      plt.rcParams['axes.grid'] = False
-      plt.rcParams['xtick.labelsize'] = False
-      plt.rcParams['ytick.labelsize'] = False
-      plt.rcParams['xtick.top'] = False
-      plt.rcParams['xtick.bottom'] = False
-      plt.rcParams['ytick.left'] = False
-      plt.rcParams['ytick.right'] = False
-      #plt.rcParams['figure.figsize'] = [7.5,5]
-      date_captured = datetime.strptime(Image.open(image.name)._getexif()[36867], '%Y:%m:%d %H:%M:%S').strftime('%Y-%m-%d %H:%M:%S')
-      context_feature, score, results = run_inference(
-          faster_rcnn_model, image.name, date_captured)
-      faster_rcnn_output_dict = results
-      context_rcnn_image, faster_rcnn_image = show_context_rcnn_inference(
-          context_rcnn_model, image.name, context_features_matrix,
-          faster_rcnn_output_dict, context_padding_size)
-      plt.subplot(1,2,1)
-      plt.imshow(faster_rcnn_image)
-      plt.title('Faster R-CNN')
-      plt.subplot(1,2,2)
-      plt.imshow(context_rcnn_image)
-      plt.title('Context R-CNN')
-      buf = io.BytesIO()
-      plt.savefig(buf, transparent=True)
-      buf.seek(0)
-      img = Image.open(buf)
-      return img
-    except Exception as e:
-      logger.exception(e)
+  plt.rcParams['axes.grid'] = False
+  plt.rcParams['xtick.labelsize'] = False
+  plt.rcParams['ytick.labelsize'] = False
+  plt.rcParams['xtick.top'] = False
+  plt.rcParams['xtick.bottom'] = False
+  plt.rcParams['ytick.left'] = False
+  plt.rcParams['ytick.right'] = False
+  plt.rcParams['figure.figsize'] = [7.5,5]
+  date_captured = datetime.strptime(Image.open(image.name)._getexif()[36867], '%Y:%m:%d %H:%M:%S').strftime('%Y-%m-%d %H:%M:%S')
+  context_feature, score, results = run_inference(
+      faster_rcnn_model, image.name, date_captured)
+  faster_rcnn_output_dict = results
+  context_rcnn_image, faster_rcnn_image = show_context_rcnn_inference(
+      context_rcnn_model, image.name, context_features_matrix,
+      faster_rcnn_output_dict, context_padding_size)
+  plt.subplot(1,2,1)
+  plt.imshow(faster_rcnn_image)
+  plt.title('Faster R-CNN')
+  plt.subplot(1,2,2)
+  plt.imshow(context_rcnn_image)
+  plt.title('Context R-CNN')
+  buf = io.BytesIO()
+  plt.savefig(buf, transparent=True)
+  buf.seek(0)
+  img = Image.open(buf)
+  return img
 examples = os.listdir('../../Examples')
 examples = ['../../Examples/' + item for item in examples]
 title="Context R-CNN"