work on obj_detect.py sample (in progress...)

diff --git a/samples/python2/obj_detect.py b/samples/python2/obj_detect.py
index 0c99c1d..27be5e8 100644 (file)
--- a/samples/python2/obj_detect.py
+++ b/samples/python2/obj_detect.py
@@ -3,17 +3,16 @@ import cv2, cv
 import common\r
 \r
 def detect(img, cascade):\r
-    min_size = (20, 20)\r
-    haar_scale = 1.1\r
-    min_neighbors = 3\r
-    haar_flags = 0\r
-    rects = cascade.detectMultiScale(img, haar_scale, min_neighbors, haar_flags, min_size)\r
+    rects = cascade.detectMultiScale(img, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))\r
     if len(rects) == 0:\r
-        return\r
+        return []\r
     rects[:,2:] += rects[:,:2]\r
     return rects\r
 \r
 def detect_turned(img, cascade):\r
+    img = cv2.cvtColor(img, cv.CV_BGR2GRAY)\r
+    img = cv2.equalizeHist(img)\r
+\r
     img_t = cv2.transpose(img)\r
     img_cw = cv2.flip(img_t, 1)\r
     img_ccw = cv2.flip(img_t, 0)\r
@@ -22,58 +21,68 @@ def detect_turned(img, cascade):
     r_ccw = detect(img_ccw, cascade)\r
 \r
     h, w = img.shape[:2]\r
-    if r_cw is not None:\r
-        r_cw[:,[0, 2]] = h - r_cw[:,[0, 2]] - 1\r
-        r_cw = r_cw[:,[1,0,3,2]]\r
-    if r_ccw is not None:\r
-        r_ccw[:,[1, 3]] = w - r_ccw[:,[1, 3]] - 1\r
-        r_ccw = r_ccw[:,[1,0,3,2]]\r
-    rects = np.vstack( [a for a in [r, r_cw, r_ccw] if a is not None] )\r
+    rects = []\r
+    rects += [(x1, y1, x2, y2, 1, 0) for x1, y1, x2, y2 in r]\r
+    rects += [(y1, h-x1-1, y2, h-x2-1, 0, -1) for x1, y1, x2, y2 in r_cw]\r
+    rects += [(w-y1-1, x1, w-y2-1, x2, 0,  1) for x1, y1, x2, y2 in r_ccw]\r
     return rects\r
 \r
-def process_image(fn, cascade):\r
-    pass\r
+def process_image(fn, cascade, extract_faces=True):\r
+    img = cv2.imread(fn)\r
+    h, w = img.shape[:2]\r
+    scale = max(h, w) / 512.0\r
+    small = cv2.resize(img, (int(w/scale), int(h/scale)), interpolation=cv2.INTER_AREA)\r
+    rects = detect_turned(small, cascade)\r
+\r
+    for i, (x1, y1, x2, y2, vx, vy) in enumerate(rects):\r
+        cv2.rectangle(small, (x1, y1), (x2, y2), (0, 255, 0))\r
+        cv2.circle(small, (x1, y1), 2, (0, 0, 255), -1)\r
+        cv2.putText(small, str(i), ((x1+x2)/2, (y1+y2)/2), cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 255, 0))\r
+\r
+    rects = np.float32(rects).reshape(-1,6)\r
+    rects[:,:4] = np.around(rects[:,:4]*scale)\r
+\r
+    faces = []\r
+    if extract_faces:\r
+        path, name, ext = common.splitfn(fn)\r
+        face_sz = 256\r
+        for i, r in enumerate(rects):\r
+            p1, p2, u = r.reshape(3, 2)\r
+            v = np.float32( [-u[1], u[0]] )\r
+            w = np.abs(p2-p1).max()\r
+            fscale = w / face_sz\r
+            p0 = 0.5*(p1+p2 - w*(u+v))\r
+            M = np.float32([u*fscale, v*fscale, p0]).T\r
+            face = cv2.warpAffine(img, M, (face_sz, face_sz), flags=cv2.WARP_INVERSE_MAP | cv2.INTER_AREA)\r
+            faces.append(face)\r
+\r
+            cv2.imwrite('out/%s_%02d.bmp' % (name, i), face)\r
+        \r
+    return small, rects, faces\r
     \r
     \r
 \r
 if __name__ == '__main__':\r
     import sys\r
     import getopt\r
+    from glob import glob\r
+\r
     args, img_mask = getopt.getopt(sys.argv[1:], '', ['cascade='])\r
     args = dict(args)\r
+    # "../../data/haarcascades/haarcascade_frontalface_default.xml" #haarcascade_frontalface_default\r
     cascade_fn = args.get('--cascade', "../../data/haarcascades/haarcascade_frontalface_alt.xml")\r
 \r
     cascade = cv2.CascadeClassifier(cascade_fn)\r
 \r
-\r
-    img = cv2.imread('test.jpg')\r
-    h, w = img.shape[:2]\r
-    r = 512.0 / max(h, w)\r
-    small = cv2.resize(img, (int(w*r), int(h*r)), interpolation=cv2.INTER_AREA)\r
-    rects = detect_turned(small, cascade)\r
-    print rects\r
-    for x1, y1, x2, y2 in rects:\r
-        cv2.rectangle(small, (x1, y1), (x2, y2), (0, 255, 0))\r
-        cv2.circle(small, (x1, y1), 2, (0, 0, 255), -1)\r
-\r
-\r
-\r
-    cv2.imshow('img', small)\r
-    cv2.waitKey()\r
+    mask = 'D:/Dropbox/Photos/2011-06-12 aero/img_08[2-9]*.jpg'\r
+    for fn in glob(mask):\r
+        print fn\r
+        vis, rects, faces = process_image(fn, cascade)\r
+        cv2.imshow('img', vis)\r
+        cv2.waitKey(100)\r
 \r
     \r
-\r
-'''\r
-\r
-\r
-    img = cv2.imread('test.jpg')\r
-    h, w = img.shape[:2]\r
-\r
-\r
-    r = 512.0 / max(h, w)\r
-    small = cv2.resize(img, (w*r, h*r), interpolation=cv2.INTER_AREA)\r
-\r
-cv2.imshow('img', small)\r
-cv2.waitKey()\r
-\r
-'''
\ No newline at end of file
+    #vis, rects = process_image('test.jpg', cascade)\r
+    #print rects\r
+    #cv2.imshow('img', vis)\r
+    cv2.waitKey()\r