diff --git a/.vscode/launch.json b/.vscode/launch.json
index ca5e2eba968104ef850e02e4c1de44a62cd21468..17e15f27ec2bb23f50627f046a7e8d1b225be974 100644
--- a/.vscode/launch.json
+++ b/.vscode/launch.json
@@ -4,13 +4,6 @@
     // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
     "version": "0.2.0",
     "configurations": [
-        {
-            "name": "Python: Main File",
-            "type": "python",
-            "request": "launch",
-            "program": "${workspaceFolder}/main.py",
-            "console": "integratedTerminal"
-        },
         {
             "name": "Python: Current File",
             "type": "python",
diff --git a/app.py b/app.py
index b1c5f47a1bcaa66421a111449070b8838323d025..15c3597d24819359a8a83460f61fcbf086258aed 100644
--- a/app.py
+++ b/app.py
@@ -1,4 +1,6 @@
 """Stream output of main.py script to index.html"""
+# import matplotlib
+# matplotlib.use('tkagg')
 import threading
 import cv2
 from flask import Flask, render_template, Response
diff --git a/settings.py b/settings.py
index 4bd6c55595ef36bbc3ddcb1219f2ddb52ebf6db9..6366ac472a6e09038f9836ae6854f781b7e31eee 100644
--- a/settings.py
+++ b/settings.py
@@ -30,7 +30,7 @@ SHAPE = (960, 1280, 3)
 TYPE = np.uint16
 
 # Blob detection size
-BLOB_SIZE = 8
+BLOB_SIZE = 9
 
 # Region of interest of the image
 REGION = np.array([[8, 466], [1260, 638]])
diff --git a/tools.py b/tools.py
index 14ae2cbcc4bb8911d9b5156c25ab2fdae6cd3a45..b10883b74021f0eb01bbaeed77884cc2fccc4ada 100644
--- a/tools.py
+++ b/tools.py
@@ -66,7 +66,6 @@ class Main:
         """
         Apply the processing on the images.
         """
-        warnings.simplefilter("once", UserWarning)
         while True:
             dist_factor = read_factor(self.conn)
             image = load_image()
@@ -118,6 +117,8 @@ class Main:
         if len(coord) > 0:
             roundness = ion_roundness(img, coord[0][:2])
             img = compensate_gradient(img, coord)
+        else:
+            roundness = -1
         max_int, num_pix = max_ion_intensity(img, coord)
         coord = detect_dim_ions(img, coord, max_int)
         linearity = ion_linearity(coord)
@@ -582,9 +583,9 @@ def dark_ions(image, coord, dist_factor):
     coord = coord[coord[:, 1].argsort()].astype(int)
     coord = coord[coord[:, 1] < image.shape[1]]  # remove points outside the image
 
-    if loss.min() > 20:
-        warnings.warn("Loss is too high... "
-        "Try calculating a new factor value using calibrate() function.")
+    # if loss.min() > 20:
+    #     warnings.warn("Loss is too high... "
+    #     "Try calculating a new factor value using calibrate() function.")
 
     return coord