Added default upsampling amount to detector.run(). Also moved the

new example code into face_detector.py and added some comments.

python_examples/face_detector.py

@@ -51,11 +51,24 @@ for f in sys.argv[1:]:
     # faces.
     dets = detector(img, 1)
     print("Number of faces detected: {}".format(len(dets)))
-    for k, d in enumerate(dets):
+    for i, d in enumerate(dets):
         print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format(
-            k, d.left(), d.top(), d.right(), d.bottom()))
+            i, d.left(), d.top(), d.right(), d.bottom()))
 
     win.clear_overlay()
     win.set_image(img)
     win.add_overlay(dets)
     dlib.hit_enter_to_continue()
+
+
+# Finally, if you really want to you can ask the detector to tell you the score
+# for each detection.  The score is bigger for more confident detections.
+# Also, the idx tells you which of the face sub-detectors matched.  This can be
+# used to broadly identify faces in different orientations.
+if (len(sys.argv[1:]) > 0):
+    img = io.imread(sys.argv[1])
+    dets, scores, idx = detector.run(img, 1)
+    for i, d in enumerate(dets):
+        print("Detection {}, score: {}, face_type:{}".format(
+            d, scores[i], idx[i]))
+

python_examples/face_detector_scores_idx.py

-
-from PIL import Image
-import numpy as np
-import dlib
-
-img = np.array(Image.open('../examples/faces/2008_002506.jpg'))
-detector = dlib.get_frontal_face_detector()
-
-dets, scores, idx = detector.run(img, 1)
-
-for i, d in enumerate(dets):
-    print d, scores[i], idx[i]
-

tools/python/src/object_detection.cpp

@@ -354,7 +354,7 @@ ensures \n\
       detector.  If you don't know how many times you want to upsample then \n\
       don't provide a value for upsample_num_times and an appropriate \n\
       default will be used.")
-        .def("run", run_rect_detector, (arg("image"), arg("upsample_num_times")),
+        .def("run", run_rect_detector, (arg("image"), arg("upsample_num_times")=0),
 "requires \n\
     - image is a numpy ndarray containing either an 8bit grayscale or RGB \n\
       image. \n\