diff --git a/script/LedDetection.py b/script/LedDetection.py
index 0c52af6..23b0d87 100644
--- a/script/LedDetection.py
+++ b/script/LedDetection.py
@@ -2,6 +2,7 @@
 # Example of using ImageJ functionalities through ijutils.
 ################################################################################################### 
 
+import datetime
 from ijutils import *
 import java.awt.Color as Color
 
@@ -21,14 +22,25 @@ def detect_led(ip):
 """
 
 roi_center = (2322, 1025)
-roi_radius = 700
-integration_count = 10
+roi_radius = 675
+integration_count = 5
 integration_continuous = False
 integration_partial = False
 frames = []            
 
+roi = (roi_center[0] - roi_radius, roi_center[1] - roi_radius, 2* roi_radius, 2*roi_radius)
 
 
+color_roi = Color(0, 128, 0)
+
+renderer = show_panel(img)
+renderer.clearOverlays()
+ov_roi_shape = Ellipse(Pen(color_roi, 0,), java.awt.Point(roi[0], roi[1]), java.awt.Dimension(roi[2], roi[3]))       
+ov_roi_bound = Rect(Pen(color_roi, 0, Pen.LineStyle.dotted), java.awt.Point(roi[0], roi[1]), java.awt.Dimension(roi[2], roi[3]))       
+ov_roi_center = Crosshairs(Pen(color_roi, 0),  java.awt.Point(roi_center[0],roi_center[1]), java.awt.Dimension(15,15))
+
+renderer.addOverlays([ov_roi_shape, ov_roi_bound,ov_roi_center])
+
     
 """
 def in_roi(x,y):
@@ -66,8 +78,6 @@ class MyFilter(Filter):
     
 """ 
 
-       
-
 def in_roi(x,y):
     return math.hypot(x-roi_radius, y-roi_radius) < roi_radius
 
@@ -75,17 +85,16 @@ def in_roi(x,y):
 def integrate (ips):    
     for i in range(len(ips)):
         if i==0:
-            aux = new_image(2* roi_radius, 2*roi_radius, image_type="float", title = "sum", fill_color = None)
+            aux = new_image(roi[2], roi[3], image_type="float", title = "sum", fill_color = None)
         op_image(aux, ips[i], "add", float_result=True, in_place=True)
     op_const(aux, "divide", len(ips), in_place=True)
     return aux
 
 last_ret = (None, None)
-
 def detect_led(ip):
     global roi_center, roi_radius, integration_count, integration_continuous, integration_partial, frames
-    global count , last_ret     
-    aux = sub_image(ip, roi_center[0] - roi_radius, roi_center[1] - roi_radius, 2* roi_radius, 2*roi_radius)
+    global count , last_ret 
+    aux = sub_image(ip, roi[0], roi[1], roi[2], roi[3])
     grayscale(aux)
     gaussian_blur(aux)
 
@@ -106,9 +115,9 @@ def detect_led(ip):
     #subtract_background(aux)
     auto_threshold(aux)
     #binary_open(aux)
-    (results,output) =  analyse_particles(aux, 400,4000, 
+    (results,output) =  analyse_particles(aux, 500,4000, 
             fill_holes = True, exclude_edges = True,print_table=False,
-            output_image = "outlines", minCirc = 0.4
+            output_image = "outlines", minCirc = 0.3
             , maxCirc = 1.0)
     r=results
 
@@ -130,8 +139,12 @@ def detect_led(ip):
     last_ret = (results,output)
     if not integration_continuous:
         frames = []  
-    return (results,aux)    
-    #return (results,output)
+
+    if r.counter==10:
+        save_image(output,  "{images}/" + str(datetime.datetime.now())+".png", "png")
+    #    output.
+    #return (results,aux)    
+    return (results,output)
 
 
 
@@ -145,7 +158,7 @@ class MyFilter(Filter):
         (results,output) = detect_led(ip)
         if output is not None:
             invert(output)
-            output = pad_image(output, roi_center[0] - roi_radius, 0, roi_center[1] - roi_radius, 0)        
+            output = pad_image(output, roi[0], 0,roi[1], 0)        
             op_image(ip, output, "xor")        
         return ip.getBufferedImage()