Add initial folder structure.

Author: jonathanrocher

face_detect_skimage.py

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+from skimage import data
+from skimage.feature import Cascade
+
+import matplotlib.pyplot as plt
+from matplotlib import patches
+
+# Load the trained file from the module root.
+trained_file = data.lbp_frontal_face_cascade_filename()
+
+# Initialize the detector cascade.
+detector = Cascade(trained_file)
+
+img = data.astronaut()
+
+detected = detector.detect_multi_scale(img=img,
+                                       scale_factor=1.2,
+                                       step_ratio=1,
+                                       min_size=(60, 60),
+                                       max_size=(123, 123))
+
+plt.imshow(img)
+img_desc = plt.gca()
+plt.set_cmap('gray')
+
+for patch in detected:
+
+    img_desc.add_patch(
+        patches.Rectangle(
+            (patch['c'], patch['r']),
+            patch['width'],
+            patch['height'],
+            fill=False,
+            color='r',
+            linewidth=2
+        )
+    )
+
+plt.show()

pycasa/__init___.py

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+import cv2
+import sys
+from matplotlib.pyplot import imshow, show
+
+
+def collect_detected_faces(image_path, casc_path=None, draw_rectangles=False,
+                           show_image=False):
+    if casc_path is None:
+        casc_path = "haarcascade_frontalface_default.xml"
+
+    # Create the haar cascade
+    face_cascade = cv2.CascadeClassifier(casc_path)
+
+    # Read the image
+    image = cv2.imread(image_path)
+    gray = cv2.imread(image_path, 0)
+
+    # Detect faces in the image
+    faces = face_cascade.detectMultiScale(
+        gray,
+        scaleFactor=1.1,
+        minNeighbors=5,
+        minSize=(30, 30)
+        # flags = cv2.CV_HAAR_SCALE_IMAGE
+    )
+    if draw_rectangles:
+        # Draw a rectangle around the faces
+        for (x, y, w, h) in faces:
+            cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2, 4)
+
+    if show_image:
+        imshow(image)
+        show()
+
+    return faces, image
+
+
+if __name__ == "__main__":
+    # Get user supplied values
+    imagePath = sys.argv[1]
+    cascPath = "haarcascade_frontalface_default.xml"
+
+    faces, image = collect_detected_faces(imagePath, draw_rectangles=True,
+                                          show_image=True)
+    print("Found {0} faces!".format(len(faces)))