f4334277
 Hu Chunming
提交3rdparty
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#!/usr/bin/env python
'''
Multitarget planar tracking
==================
Example of using features2d framework for interactive video homography matching.
ORB features and FLANN matcher are used. This sample provides PlaneTracker class
and an example of its usage.
video: http://www.youtube.com/watch?v=pzVbhxx6aog
Usage
-----
plane_tracker.py [<video source>]
Keys:
SPACE - pause video
c - clear targets
Select a textured planar object to track by drawing a box with a mouse.
'''
# Python 2/3 compatibility
from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
import numpy as np
import cv2 as cv
# built-in modules
from collections import namedtuple
# local modules
import video
import common
from video import presets
FLANN_INDEX_KDTREE = 1
FLANN_INDEX_LSH = 6
flann_params= dict(algorithm = FLANN_INDEX_LSH,
table_number = 6, # 12
key_size = 12, # 20
multi_probe_level = 1) #2
MIN_MATCH_COUNT = 10
'''
image - image to track
rect - tracked rectangle (x1, y1, x2, y2)
keypoints - keypoints detected inside rect
descrs - their descriptors
data - some user-provided data
'''
PlanarTarget = namedtuple('PlaneTarget', 'image, rect, keypoints, descrs, data')
'''
target - reference to PlanarTarget
p0 - matched points coords in target image
p1 - matched points coords in input frame
H - homography matrix from p0 to p1
quad - target boundary quad in input frame
'''
TrackedTarget = namedtuple('TrackedTarget', 'target, p0, p1, H, quad')
class PlaneTracker:
def __init__(self):
self.detector = cv.ORB_create( nfeatures = 1000 )
self.matcher = cv.FlannBasedMatcher(flann_params, {}) # bug : need to pass empty dict (#1329)
self.targets = []
self.frame_points = []
def add_target(self, image, rect, data=None):
'''Add a new tracking target.'''
x0, y0, x1, y1 = rect
raw_points, raw_descrs = self.detect_features(image)
points, descs = [], []
for kp, desc in zip(raw_points, raw_descrs):
x, y = kp.pt
if x0 <= x <= x1 and y0 <= y <= y1:
points.append(kp)
descs.append(desc)
descs = np.uint8(descs)
self.matcher.add([descs])
target = PlanarTarget(image = image, rect=rect, keypoints = points, descrs=descs, data=data)
self.targets.append(target)
def clear(self):
'''Remove all targets'''
self.targets = []
self.matcher.clear()
def track(self, frame):
'''Returns a list of detected TrackedTarget objects'''
self.frame_points, frame_descrs = self.detect_features(frame)
if len(self.frame_points) < MIN_MATCH_COUNT:
return []
matches = self.matcher.knnMatch(frame_descrs, k = 2)
matches = [m[0] for m in matches if len(m) == 2 and m[0].distance < m[1].distance * 0.75]
if len(matches) < MIN_MATCH_COUNT:
return []
matches_by_id = [[] for _ in xrange(len(self.targets))]
for m in matches:
matches_by_id[m.imgIdx].append(m)
tracked = []
for imgIdx, matches in enumerate(matches_by_id):
if len(matches) < MIN_MATCH_COUNT:
continue
target = self.targets[imgIdx]
p0 = [target.keypoints[m.trainIdx].pt for m in matches]
p1 = [self.frame_points[m.queryIdx].pt for m in matches]
p0, p1 = np.float32((p0, p1))
H, status = cv.findHomography(p0, p1, cv.RANSAC, 3.0)
status = status.ravel() != 0
if status.sum() < MIN_MATCH_COUNT:
continue
p0, p1 = p0[status], p1[status]
x0, y0, x1, y1 = target.rect
quad = np.float32([[x0, y0], [x1, y0], [x1, y1], [x0, y1]])
quad = cv.perspectiveTransform(quad.reshape(1, -1, 2), H).reshape(-1, 2)
track = TrackedTarget(target=target, p0=p0, p1=p1, H=H, quad=quad)
tracked.append(track)
tracked.sort(key = lambda t: len(t.p0), reverse=True)
return tracked
def detect_features(self, frame):
'''detect_features(self, frame) -> keypoints, descrs'''
keypoints, descrs = self.detector.detectAndCompute(frame, None)
if descrs is None: # detectAndCompute returns descs=None if not keypoints found
descrs = []
return keypoints, descrs
class App:
def __init__(self, src):
self.cap = video.create_capture(src, presets['book'])
self.frame = None
self.paused = False
self.tracker = PlaneTracker()
cv.namedWindow('plane')
self.rect_sel = common.RectSelector('plane', self.on_rect)
def on_rect(self, rect):
self.tracker.add_target(self.frame, rect)
def run(self):
while True:
playing = not self.paused and not self.rect_sel.dragging
if playing or self.frame is None:
ret, frame = self.cap.read()
if not ret:
break
self.frame = frame.copy()
vis = self.frame.copy()
if playing:
tracked = self.tracker.track(self.frame)
for tr in tracked:
cv.polylines(vis, [np.int32(tr.quad)], True, (255, 255, 255), 2)
for (x, y) in np.int32(tr.p1):
cv.circle(vis, (x, y), 2, (255, 255, 255))
self.rect_sel.draw(vis)
cv.imshow('plane', vis)
ch = cv.waitKey(1)
if ch == ord(' '):
self.paused = not self.paused
if ch == ord('c'):
self.tracker.clear()
if ch == 27:
break
if __name__ == '__main__':
print(__doc__)
import sys
try:
video_src = sys.argv[1]
except:
video_src = 0
App(video_src).run()
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