work on feature_homography.py: multiple targets

diff --git a/samples/python2/common.py b/samples/python2/common.py
index 0f332b6..6b62f43 100644 (file)
--- a/samples/python2/common.py
+++ b/samples/python2/common.py
@@ -6,6 +6,12 @@ import itertools as it
 \r
 image_extensions = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.pbm', '.pgm', '.ppm']\r
 \r
+class Bunch(object):\r
+    def __init__(self, **kw):\r
+        self.__dict__.update(kw)\r
+    def __str__(self):\r
+        return str(self.__dict__)\r
+\r
 def splitfn(fn):\r
     path, fn = os.path.split(fn)\r
     name, ext = os.path.splitext(fn)\r

diff --git a/samples/python2/feature_homography.py b/samples/python2/feature_homography.py
index d553deb..182b569 100644 (file)
--- a/samples/python2/feature_homography.py
+++ b/samples/python2/feature_homography.py
@@ -20,7 +20,7 @@ import cv2
 import video\r
 import common\r
 from collections import namedtuple\r
-from common import getsize\r
+from common import getsize, Bunch\r
 \r
     \r
 FLANN_INDEX_KDTREE = 1\r
@@ -35,11 +35,11 @@ MIN_MATCH_COUNT = 10
 \r
 ar_verts = np.float32([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0],\r
                        [0, 0, 1], [0, 1, 1], [1, 1, 1], [1, 0, 1], \r
-                       [0.5, 0.5, 2]])\r
+                       [0, 0.5, 2], [1, 0.5, 2]])\r
 ar_edges = [(0, 1), (1, 2), (2, 3), (3, 0), \r
             (4, 5), (5, 6), (6, 7), (7, 4),\r
             (0, 4), (1, 5), (2, 6), (3, 7), \r
-            (4, 8), (5, 8), (6, 8), (7, 8)]\r
+            (4, 8), (5, 8), (6, 9), (7, 9), (8, 9)]\r
 \r
 \r
 \r
@@ -53,7 +53,7 @@ class App:
         self.cap = video.create_capture(src)\r
         self.frame = None\r
         self.paused = False\r
-        self.ref_frame  = None\r
+        self.ref_frames = []\r
 \r
         self.detector = cv2.ORB( nfeatures = 1000 )\r
         self.matcher = cv2.FlannBasedMatcher(flann_params, {})  # bug : need to pass empty dict (#1329)\r
@@ -66,13 +66,19 @@ class App:
         if len(self.frame_desc) < MIN_MATCH_COUNT or len(self.frame_desc) < MIN_MATCH_COUNT:\r
             return\r
         \r
-        raw_matches = self.matcher.knnMatch(self.frame_desc, k = 2)\r
-        p0, p1 = [], []\r
-        for m in raw_matches:\r
-            if len(m) == 2 and m[0].distance < m[1].distance * 0.75:\r
-                m = m[0]\r
-                p0.append( self.ref_points[m.trainIdx].pt )  # queryIdx\r
-                p1.append( self.frame_points[m.queryIdx].pt )\r
+        matches = self.matcher.knnMatch(self.frame_desc, k = 2)\r
+        matches = [m[0] for m in matches if len(m) == 2 and m[0].distance < m[1].distance * 0.75]\r
+        if len(matches) < MIN_MATCH_COUNT:\r
+            return\r
+        img_ids = [m.imgIdx for m in matches]\r
+        match_counts = np.bincount(img_ids, minlength=len(self.ref_frames))\r
+        bast_id = match_counts.argmax()\r
+        if match_counts[bast_id] < MIN_MATCH_COUNT:\r
+            return\r
+        ref_frame = self.ref_frames[bast_id]\r
+        matches = [m for m in matches if m.imgIdx == bast_id]\r
+        p0 = [ref_frame.points[m.trainIdx].pt for m in matches]\r
+        p1 = [self.frame_points[m.queryIdx].pt for m in matches]\r
         p0, p1 = np.float32((p0, p1))\r
         if len(p0) < MIN_MATCH_COUNT:\r
             return\r
@@ -82,22 +88,28 @@ class App:
         if status.sum() < MIN_MATCH_COUNT:\r
             return\r
         p0, p1 = p0[status], p1[status]\r
-        return p0, p1, H\r
+        return ref_frame, p0, p1, H\r
 \r
 \r
     def on_frame(self, vis):\r
         match = self.match_frames()\r
         if match is None:\r
             return\r
+        \r
         w, h = getsize(self.frame)\r
-        p0, p1, H = match\r
-        for (x0, y0), (x1, y1) in zip(np.int32(p0), np.int32(p1)):\r
-            cv2.line(vis, (x0+w, y0), (x1, y1), (0, 255, 0))\r
-        x0, y0, x1, y1 = self.ref_rect\r
+        ref_frame, p0, p1, H = match\r
+        vis[:h,w:] = ref_frame.frame\r
+        draw_keypoints(vis[:,w:], ref_frame.points)\r
+        x0, y0, x1, y1 = ref_frame.rect\r
+        cv2.rectangle(vis, (x0+w, y0), (x1+w, y1), (0, 255, 0), 2)\r
         corners0 = np.float32([[x0, y0], [x1, y0], [x1, y1], [x0, y1]])\r
         img_corners = cv2.perspectiveTransform(corners0.reshape(1, -1, 2), H)\r
         cv2.polylines(vis, [np.int32(img_corners)], True, (255, 255, 255), 2)\r
 \r
+        for (x0, y0), (x1, y1) in zip(np.int32(p0), np.int32(p1)):\r
+            cv2.line(vis, (x0+w, y0), (x1, y1), (0, 255, 0))\r
+\r
+        '''\r
         corners3d = np.hstack([corners0, np.zeros((4, 1), np.float32)])\r
         fx = 0.9\r
         K = np.float64([[fx*w, 0, 0.5*(w-1)],\r
@@ -110,21 +122,19 @@ class App:
         for i, j in ar_edges:\r
             (x0, y0), (x1, y1) = verts[i], verts[j]\r
             cv2.line(vis, (int(x0), int(y0)), (int(x1), int(y1)), (255, 255, 0), 2)\r
-\r
+        '''\r
     def on_rect(self, rect):\r
         x0, y0, x1, y1 = rect\r
-        self.ref_frame = self.frame.copy()\r
-        self.ref_rect = rect\r
         points, descs = [], []\r
         for kp, desc in zip(self.frame_points, self.frame_desc):\r
             x, y = kp.pt\r
             if x0 <= x <= x1 and y0 <= y <= y1:\r
                 points.append(kp)\r
                 descs.append(desc)\r
-        self.ref_points, self.ref_descs = points, np.uint8(descs)\r
-\r
-        self.matcher.clear()\r
-        self.matcher.add([self.ref_descs])\r
+        descs = np.uint8(descs)\r
+        frame_data = Bunch(frame = self.frame, rect=rect, points = points, descs=descs)\r
+        self.ref_frames.append(frame_data)\r
+        self.matcher.add([descs])\r
 \r
     def run(self):\r
         while True:\r
@@ -141,14 +151,9 @@ class App:
             w, h = getsize(self.frame)\r
             vis = np.zeros((h, w*2, 3), np.uint8)\r
             vis[:h,:w] = self.frame\r
-            if self.ref_frame is not None:\r
-                vis[:h,w:] = self.ref_frame\r
-                x0, y0, x1, y1 = self.ref_rect\r
-                cv2.rectangle(vis, (x0+w, y0), (x1+w, y1), (0, 255, 0), 2)\r
-                draw_keypoints(vis[:,w:], self.ref_points)\r
             draw_keypoints(vis, self.frame_points)\r
 \r
-            if playing and self.ref_frame is not None:\r
+            if playing:\r
                 self.on_frame(vis)\r
             \r
             self.rect_sel.draw(vis)\r