Better white calibration

rasp_app/main.py

@@ -4,7 +4,7 @@
 import time
 import sqlite3 as lite
 import scipy.signal as sps
-from matplotlib.pylab import savefig
+#from matplotlib.pylab import savefig
 from PIL import Image
 import datetime
 from signal_processing import *
@@ -33,9 +33,6 @@ def data_taken():
     TODO: return also machine learning prediction
     """
 
-    if( not os.path.isfile(HOME_PATH + '/white_cal.txt')):
-        return "NO,,White calibration is needed"
-
     fruit = int(request.form.get('fruit'))
     gps = request.form.get('gps')
     if gps == None:
@@ -78,7 +75,7 @@ def take_data(fruit):
     ----------
     - The confirmation HTML page
     """
-    if(not os.path.isfile(HOME_PATH + '/static/processed_white.jpg')):
+    if(not os.path.isfile(HOME_PATH + '/static/processed_white.png')):
         get_white = 1
     else:
         get_white = 0
@@ -349,8 +346,8 @@ def calibrate_white_done():
         os.system("mkdir " + HOME_PATH + '/configuration')
     if(not os.path.isdir(HOME_PATH + '/temp_data')):
         os.system("mkdir " + HOME_PATH + '/temp_data')
-    if(os.path.isfile(HOME_PATH + '/static/processed_white.jpg')):
-        os.system("rm " + HOME_PATH + '/static/processed_white.jpg')
+    if(os.path.isfile(HOME_PATH + '/static/processed_white.png')):
+        os.system("rm " + HOME_PATH + '/static/processed_white.png')
     if(not os.path.isfile(HOME_PATH + '/timestamp.txt')):
         out_file = open(HOME_PATH + '/timestamp.txt',"w")
         out_file.write(str(0))

rasp_app/signal_processing.py

@@ -17,6 +17,7 @@
 
 HOME_PATH  = os.path.dirname(os.path.abspath(__file__))
 
+#This function could be also be deleted since it isn't used
 def mins(array,wl):
     """
     This function receive as input the spectrum and the wavelenghts.
@@ -140,7 +141,7 @@ def save_plot(array, wl=[],controls=0):
     return script, div
 
 
-def get_image(new_photo = 0, white_calibration = 0):
+def get_image(new_photo = False, white_calibration = False):
     """
     This function receive as input some parameters as a tuple.
     The return value is the image of the spectrum.
@@ -166,13 +167,15 @@ def get_image(new_photo = 0, white_calibration = 0):
     im=Image.open(HOME_PATH + '/source.jpg')
     im=im.rotate(param[4])
     im = im.crop(box=param[:4])
+
+    #We need to save the spectra as PNG because the JPG compress them altering the data
     if white_calibration:
-        im.save(HOME_PATH + '/static/processed_white.jpg')
+        im.save(HOME_PATH + '/static/processed_white.png')
     else:
-        im.save(HOME_PATH + '/static/processed.jpg')
+        im.save(HOME_PATH + '/static/processed.png')
 
-    #Better not to resize, data is lost or altered too much
     #maxsize = (1000, im.size[0])
+    #Better not to resize, data is lost or altered too much
     #im = im.resize(maxsize, Image.ANTIALIAS)
 
     #im.show()
@@ -207,7 +210,7 @@ def filter_white(baseline):
     ----------
     :value 0: List of y elements of the spectrum
     """
-    im=Image.open(HOME_PATH + '/source.jpg')
+    im=Image.open(HOME_PATH + '/static/processed_white.png')
     img_white = im.load()
 
     param=get_params()
@@ -221,10 +224,11 @@ def filter_white(baseline):
             r,g,b = img_white[col,row]
             tot[col].append(r+g+b)
 
-    for i in range(tot):
-        baseline = max(tot[i]) / baseline[i]
+    filtered = []
+    for to,ba in zip(tot,baseline):
+        filtered.append(max(to) / ba)
 
-    return baseline
+    return filtered
 
 def get_baseline(img_spectrum):
     """
@@ -298,13 +302,18 @@ def process_image(white_spectrum = 0):
     img_spectrum = get_image(new_photo=1)
 
     baseline = get_baseline(img_spectrum)
-    filtered = filter_white(baseline)
+    #filtered = filter_white(baseline)
+
+    filtered = baseline #Uncomment not to use white calibration and get only raw values
+
     #plt.plot(black_line, color="blue")
+    #print(baseline)
+    #print()
+    #print(filtered)
     almost_good = sps.savgol_filter(filtered, 51, 3)
     #plt.plot(almost_good, color="red")
     #savefig(HOME_PATH + '/aabbbccc.png', bbox_inches='tight')
-    wl = np.array(range(400,801))
-    idx = mins(almost_good,wl)
+    wl = np.array(range(400,651))
 
     background_rem = remove_background(almost_good)
 
@@ -360,8 +369,8 @@ def normalize(array, wl):
     param = get_spectrum_param()
     diff_param = param[1] - param[0]
 
-    begin = param[0] - diff_param * 0.75
-    end = param[1] + diff_param * 2.25
+    begin = param[0] - diff_param * 0.327
+    end = param[1] + diff_param * 0.945
 
     begin_px = int(begin*len(array)/1000)
     end_px = int(end*len(array)/1000)