static/image

dip.py
final.py

detection.py

@@ -0,0 +1,52 @@
+import sys, os
+from opencv.cv import *
+from opencv.highgui import *
+
+def detectObjects(image):
+  """Converts an image to grayscale and prints the locations of any 
+     faces found"""
+  grayscale = cvCreateImage(cvSize(image.width, image.height), 8, 1)
+  cvCvtColor(image, grayscale, CV_BGR2GRAY)
+
+  storage = cvCreateMemStorage(0)
+  cvClearMemStorage(storage)
+  cvEqualizeHist(grayscale, grayscale)
+  #cascade = cvLoadHaarClassifierCascade('haarcascade_frontalface_alt2.xml', cvSize(1,1))
+  #cascade = cvLoadHaarClassifierCascade('haarcascade_frontalface_alt2.xml', cvSize(1,1))
+  cascade = cvLoadHaarClassifierCascade('haarcascade_frontalface_alt2.xml',cvSize(1,1))
+  cascade_eyes = cvLoadHaarClassifierCascade('haarcascade_mcs_eyepair_big.xml',cvSize(1,1))
+  cascade_nose = cvLoadHaarClassifierCascade('haarcascade_mcs_nose.xml',cvSize(1,1))
+  cascade_mouth = cvLoadHaarClassifierCascade('haarcascade_mcs_mouth.xml',cvSize(1,1))
+
+  #faces = cvHaarDetectObjects(img,cascade, storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(20, 20));
+  #faces = cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(50,50))
+  faces = cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(50,50))
+  eyes = cvHaarDetectObjects(grayscale, cascade_eyes, storage, 1.15, 3, 0, cvSize(25,15))
+  nose = cvHaarDetectObjects(grayscale, cascade_nose, storage, 1.15, 3, 0, cvSize(25,15))
+  mouth = cvHaarDetectObjects(grayscale, cascade_mouth, storage, 1.15, 4, 0, cvSize(25,15))
+
+  print "faces"
+  if faces:
+    for f in faces:
+      print("[(%d,%d) -> (%d,%d)]" % (f.x, f.y, f.x+f.width, f.y+f.height))
+  print "eyes"
+  if eyes:
+    for f in eyes:
+      print("[(%d,%d) -> (%d,%d)]" % (f.x, f.y, f.x+f.width, f.y+f.height))
+  print "nose"
+  if nose:
+    for f in nose:
+      print("[(%d,%d) -> (%d,%d)]" % (f.x, f.y, f.x+f.width, f.y+f.height))
+  print "mouth"
+  if mouth:
+    for f in mouth:
+      print("[(%d,%d) -> (%d,%d)]" % (f.x, f.y, f.x+f.width, f.y+f.height))
+
+
+
+def main():
+  image = cvLoadImage(sys.argv[1]);
+  detectObjects(image)
+
+if __name__ == "__main__":
+  main()

dip.py

@@ -21,22 +21,24 @@ def get(self):
     def post(self):
         print self.request.arguments
         lines = []
-        for x in self.request.arguments['lines'][0].split():
-            tmp = x.split(',')
-            line = [[float(tmp[0]), float(tmp[1])], [float(tmp[2]), float(tmp[3])]]
-            lines.append(line)
-        #print lines
+	if 'lines' in self.request.arguments:
+		for x in self.request.arguments['lines'][0].split():
+		    tmp = x.split(',')
+		    line = [[float(tmp[0]), float(tmp[1])], [float(tmp[2]), float(tmp[3])]]
+		    lines.append(line)
+		#print lines
 
         rlines = []
-        for x in self.request.arguments['rlines'][0].split():
-            tmp = x.split(',')
-            rline = [[float(tmp[0]), float(tmp[1])], [float(tmp[2]), float(tmp[3])]]
-            rlines.append(rline)
+	if 'rlines' in self.request.arguments:
+		for x in self.request.arguments['rlines'][0].split():
+		    tmp = x.split(',')
+		    rline = [[float(tmp[0]), float(tmp[1])], [float(tmp[2]), float(tmp[3])]]
+		    rlines.append(rline)
 
         #print rlines
 
         out = final.inputImage(self.request.arguments['left'][0], self.request.arguments['right'][0], lines, rlines, 0.5, 1, 1, 2)
-        out.save('test.jpg', quality = 100)
+        #out.save('test.jpg', quality = 100)
         #jpg_temp = splitext(jpg1)[0]+"_Resized1.jpg"
         #nim.save(jpg_temp, quality = 100)