Changes Project Structure to get a cleaner architecture

test/face_script.py

@@ -0,0 +1,91 @@
+'''
+Created on 27 mars 2012
+
+@author: jll
+Adaptation from a code found here : 
+http://japskua.wordpress.com/2010/08/04/detecting-eyes-with-python-opencv/
+'''
+import cv
+
+def detectRedEyes(image, faceCascade, eyeCascade):
+    min_size = (20,20)
+    image_scale = 2
+    haar_scale = 1.2
+    min_neighbors = 2
+    haar_flags = 0
+
+    # Allocate the temporary images
+    gray = cv.CreateImage((image.width, image.height), 8, 1)
+    smallImage = cv.CreateImage((cv.Round(image.width / image_scale),
+                                 cv.Round (image.height / image_scale)), 8 ,1)
+    # Convert color input image to grayscale
+    cv.CvtColor(image, gray, cv.CV_BGR2GRAY)
+    # Scale input image for faster processing
+    cv.Resize(gray, smallImage, cv.CV_INTER_LINEAR)
+    # Equalize the histogram
+    cv.EqualizeHist(smallImage, smallImage)
+    
+    # Detect the faces
+    faces = cv.HaarDetectObjects(smallImage, faceCascade, cv.CreateMemStorage(0),
+                                 haar_scale, min_neighbors, haar_flags, min_size)
+
+    # If faces are found
+    if faces:
+        for ((x, y, w, h), n) in faces:
+            # the input to cv.HaarDetectObjects was resized, so scale the
+            # bounding box of each face and convert it to two CvPoints
+            pt1 = (int(x * image_scale), int(y * image_scale))
+            pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
+            cv.Rectangle(image, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)# If faces are found
+
+    # Estimate the eyes position
+    # First, set the image region of interest
+    # The last division removes the lower part of the face to lower probability for false recognition
+    cv.SetImageROI(image, (pt1[0],
+                           pt1[1],
+                           pt2[0] - pt1[0],
+                           int((pt2[1] - pt1[1]) * 0.6)))
+
+    # Detect the eyes
+    eyes = cv.HaarDetectObjects(image, eyeCascade,
+                                cv.CreateMemStorage(0),
+                                haar_scale, min_neighbors,
+                                haar_flags, (20,15))
+    # If eyes were found
+    if eyes:
+        # For each eye found
+        for eye in eyes:
+            # Draw a rectangle around the eye
+            cv.Rectangle(image,
+                         (eye[0][0],
+                          eye[0][1]),
+                         (eye[0][0] + eye[0][2],
+                          eye[0][1] + eye[0][3]),
+                         cv.RGB(255, 0, 0), 1, 8, 0)
+
+    # Finally, reset the image region of interest (otherwise this won t
+    # be drawn correctly
+    cv.ResetImageROI(image)
+
+    return image
+
+
+def load():
+
+    image = cv.LoadImage("input/Axel/2012-01-12-13h54m34DSCN9766.JPG")
+    faceCascade = cv.Load("haarcascades/haarcascade_frontalface_alt.xml")
+    eyeCascade = cv.Load("haarcascades/haarcascade_eye.xml")
+    return (image, faceCascade, eyeCascade)
+
+def display(image):
+    cv.NamedWindow("Red Eye Test", cv.CV_WINDOW_AUTOSIZE)
+    cv.ResizeWindow("Red Eye Test", 10, 10)
+    cv.ShowImage("Red Eye Test", image)
+    cv.WaitKey(0)
+    cv.DestroyWindow("Red Eye Test")
+
+if __name__ == '__main__':
+    print "test"
+    image, faceCascade, eyeCascade = load()
+    image = detectRedEyes(image, faceCascade, eyeCascade)
+    display(image)

test/test_script.py

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+'''
+Created on 16 avr. 2012
+
+@author: jll
+'''
+my_dict = {'a b c':1, 'b':2, 'c':3}
+print my_dict['a b c']