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108 lines
3.4 KiB
Python
Executable File
108 lines
3.4 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Planar augmented reality
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==================
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This sample shows an example of augmented reality overlay over a planar object
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tracked by PlaneTracker from plane_tracker.py. solvePnP funciton is used to
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estimate the tracked object location in 3d space.
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video: http://www.youtube.com/watch?v=pzVbhxx6aog
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Usage
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-----
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plane_ar.py [<video source>]
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Keys:
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SPACE - pause video
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c - clear targets
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Select a textured planar object to track by drawing a box with a mouse.
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Use 'focal' slider to adjust to camera focal length for proper video augmentation.
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'''
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import numpy as np
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import cv2
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import video
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import common
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from plane_tracker import PlaneTracker
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ar_verts = np.float32([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0],
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[0, 0, 1], [0, 1, 1], [1, 1, 1], [1, 0, 1],
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[0, 0.5, 2], [1, 0.5, 2]])
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ar_edges = [(0, 1), (1, 2), (2, 3), (3, 0),
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(4, 5), (5, 6), (6, 7), (7, 4),
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(0, 4), (1, 5), (2, 6), (3, 7),
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(4, 8), (5, 8), (6, 9), (7, 9), (8, 9)]
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class App:
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def __init__(self, src):
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self.cap = video.create_capture(src)
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self.frame = None
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self.paused = False
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self.tracker = PlaneTracker()
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cv2.namedWindow('plane')
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cv2.createTrackbar('focal', 'plane', 25, 50, common.nothing)
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self.rect_sel = common.RectSelector('plane', self.on_rect)
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def on_rect(self, rect):
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self.tracker.add_target(self.frame, rect)
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def run(self):
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while True:
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playing = not self.paused and not self.rect_sel.dragging
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if playing or self.frame is None:
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ret, frame = self.cap.read()
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if not ret:
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break
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self.frame = frame.copy()
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vis = self.frame.copy()
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if playing:
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tracked = self.tracker.track(self.frame)
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for tr in tracked:
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cv2.polylines(vis, [np.int32(tr.quad)], True, (255, 255, 255), 2)
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for (x, y) in np.int32(tr.p1):
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cv2.circle(vis, (x, y), 2, (255, 255, 255))
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self.draw_overlay(vis, tr)
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self.rect_sel.draw(vis)
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cv2.imshow('plane', vis)
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ch = cv2.waitKey(1) & 0xFF
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if ch == ord(' '):
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self.paused = not self.paused
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if ch == ord('c'):
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self.tracker.clear()
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if ch == 27:
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break
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def draw_overlay(self, vis, tracked):
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x0, y0, x1, y1 = tracked.target.rect
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quad_3d = np.float32([[x0, y0, 0], [x1, y0, 0], [x1, y1, 0], [x0, y1, 0]])
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fx = 0.5 + cv2.getTrackbarPos('focal', 'plane') / 50.0
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h, w = vis.shape[:2]
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K = np.float64([[fx*w, 0, 0.5*(w-1)],
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[0, fx*w, 0.5*(h-1)],
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[0.0,0.0, 1.0]])
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dist_coef = np.zeros(4)
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ret, rvec, tvec = cv2.solvePnP(quad_3d, tracked.quad, K, dist_coef)
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verts = ar_verts * [(x1-x0), (y1-y0), -(x1-x0)*0.3] + (x0, y0, 0)
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verts = cv2.projectPoints(verts, rvec, tvec, K, dist_coef)[0].reshape(-1, 2)
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for i, j in ar_edges:
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(x0, y0), (x1, y1) = verts[i], verts[j]
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cv2.line(vis, (int(x0), int(y0)), (int(x1), int(y1)), (255, 255, 0), 2)
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if __name__ == '__main__':
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print __doc__
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import sys
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try:
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video_src = sys.argv[1]
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except:
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video_src = 0
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App(video_src).run()
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