Script execution

script/CoverDetection.py

@@ -8,13 +8,11 @@ line = load_image("{images}/line.png", title="Line")
 
 line.getProcessor().setBackgroundValue(0.0)
 
-#renderer = show_panel(line.bufferedImage)
+
 #ip = get_image()
-
 ip = integrate_frames(10)
+ip = grayscale(ip, True)
 
-#ip = grayscale(ip, True)
-show_panel(ip.bufferedImage)
 
 smooth(ip)
 #bandpass_filter(ip, 30, 1000)
@@ -58,7 +56,6 @@ renderer = show_panel(ip.bufferedImage)
 
 #renderer = show_panel(op.bufferedImage)
 #line.show()
-"""
 vals = []
 for i in range (180):
     l = line.duplicate()
@@ -71,8 +68,31 @@ for i in range (180):
     
     #renderer = show_panel(op.bufferedImage)
     #time.sleep(0.001)
-plot(vals)
-"""
+p = plot(vals)[0]
+
+
+
+threshold = (min(vals) + max(vals))/2
+min_peak_distance = 10.0
+xdata=Arr.indexesInt(len(vals))
+
+peaks = estimate_peak_indexes(vals, xdata, threshold, min_peak_distance)
+print "Peak indexes: " + str(peaks)
+print "Peak x: " + str(map(lambda x:xdata[x], peaks))
+print "Peak y: " + str(map(lambda x:vals[x], peaks))
+
+gaussians = fit_gaussians(vals, xdata, peaks)
+
+for i in range(len(peaks)):
+    peak = peaks[i]
+    (normalization, mean_val, sigma) = gaussians[i]
+    if abs(mean_val - xdata[peak]) < min_peak_distance:
+        print "Peak -> " +  str(mean_val)
+        p.addMarker(mean_val, None, "N="+str(round(normalization,2)), Color(210,0,0))
+    else:
+        print "Invalid gaussian fit: " +  str(mean_val)
+
+
 #image_fft(ip)