work on digits_video.py

diff --git a/samples/python2/digits_video.py b/samples/python2/digits_video.py
index 04b272f..a66abd2 100644 (file)
--- a/samples/python2/digits_video.py
+++ b/samples/python2/digits_video.py
@@ -28,7 +28,6 @@ def main():
         bin = cv2.medianBlur(bin, 3)\r
         contours, _ = cv2.findContours( bin.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\r
 \r
-        boxes = []\r
         for cnt in contours:\r
             x, y, w, h = cv2.boundingRect(cnt)\r
             if h < 16 or h > 60 or 1.2*h < w:\r
@@ -44,7 +43,6 @@ def main():
             if m00/255 < 0.1*w*h or m00/255 > 0.9*w*h:\r
                 continue\r
 \r
-            #frame[y:,x:][:h,:w] = sub[...,np.newaxis]\r
             c1 = np.float32([m['m10'], m['m01']]) / m00\r
             c0 = np.float32([SZ/2, SZ/2])\r
             t = c1 - s*c0\r
@@ -53,17 +51,14 @@ def main():
             A[:,2] = t\r
             sub1 = cv2.warpAffine(sub, A, (SZ, SZ), flags=cv2.WARP_INVERSE_MAP | cv2.INTER_LINEAR)\r
             sub1 = digits.deskew(sub1)\r
+            if x+w+SZ < frame.shape[1] and y+SZ < frame.shape[0]:\r
+                frame[y:,x+w:][:SZ, :SZ] = sub1[...,np.newaxis]\r
+                \r
             sample = np.float32(sub1).reshape(1,SZ*SZ) / 255.0\r
             digit = model.predict(sample)[0]\r
 \r
             cv2.putText(frame, '%d'%digit, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 0, 0), thickness = 1)\r
 \r
-            boxes.append(sub1)\r
-\r
-\r
-        if len(boxes) > 0:\r
-            cv2.imshow('box', mosaic(10, boxes))\r
-            \r
 \r
         cv2.imshow('frame', frame)\r
         cv2.imshow('bin', bin)\r