feature_homography.py:
building descriptor index on target capture simple AR experiment (work in progress)
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@ -19,11 +19,8 @@ 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 operator import attrgetter
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def get_size(a):
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h, w = a.shape[:2]
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return w, h
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from collections import namedtuple
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from common import getsize
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FLANN_INDEX_KDTREE = 1
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@ -33,12 +30,29 @@ flann_params= dict(algorithm = FLANN_INDEX_LSH,
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key_size = 12, # 20
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multi_probe_level = 1) #2
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MIN_MATCH_COUNT = 10
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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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[0.5, 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, 8), (7, 8)]
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def draw_keypoints(vis, keypoints, color = (0, 255, 255)):
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for kp in keypoints:
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x, y = kp.pt
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cv2.circle(vis, (int(x), int(y)), 2, color)
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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.ref_frame = None
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self.detector = cv2.ORB( nfeatures = 1000 )
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@ -47,19 +61,18 @@ class App:
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cv2.namedWindow('plane')
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self.rect_sel = common.RectSelector('plane', self.on_rect)
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self.frame = None
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def match_frames(self):
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if len(self.frame_desc) < MIN_MATCH_COUNT or len(self.frame_desc) < MIN_MATCH_COUNT:
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return
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raw_matches = self.matcher.knnMatch(self.ref_descs, trainDescriptors = self.frame_desc, k = 2)
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raw_matches = self.matcher.knnMatch(self.frame_desc, k = 2)
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p0, p1 = [], []
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for m in raw_matches:
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if len(m) == 2 and m[0].distance < m[1].distance * 0.75:
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m = m[0]
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p0.append( self.ref_points[m.queryIdx].pt )
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p1.append( self.frame_points[m.trainIdx].pt )
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p0.append( self.ref_points[m.trainIdx].pt ) # queryIdx
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p1.append( self.frame_points[m.queryIdx].pt )
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p0, p1 = np.float32((p0, p1))
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if len(p0) < MIN_MATCH_COUNT:
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return
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@ -72,44 +85,31 @@ class App:
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return p0, p1, H
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def on_frame(self, frame):
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if self.frame is None or not self.rect_sel.dragging:
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self.frame = frame = np.fliplr(frame).copy()
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self.frame_points, self.frame_desc = self.detector.detectAndCompute(self.frame, None)
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if self.frame_desc is None: # detectAndCompute returns descs=None if not keypoints found
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self.frame_desc = []
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else:
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self.ref_frame = None
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def on_frame(self, vis):
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match = self.match_frames()
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if match is None:
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return
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w, h = getsize(self.frame)
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p0, p1, H = match
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for (x0, y0), (x1, y1) in zip(np.int32(p0), np.int32(p1)):
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cv2.line(vis, (x0+w, y0), (x1, y1), (0, 255, 0))
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x0, y0, x1, y1 = self.ref_rect
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corners0 = np.float32([[x0, y0], [x1, y0], [x1, y1], [x0, y1]])
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img_corners = cv2.perspectiveTransform(corners0.reshape(1, -1, 2), H)
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cv2.polylines(vis, [np.int32(img_corners)], True, (255, 255, 255), 2)
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w, h = get_size(self.frame)
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vis = np.zeros((h, w*2, 3), np.uint8)
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vis[:h,:w] = self.frame
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self.rect_sel.draw(vis)
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for kp in self.frame_points:
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x, y = kp.pt
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cv2.circle(vis, (int(x), int(y)), 2, (0, 255, 255))
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if self.ref_frame is not None:
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vis[:h,w:] = self.ref_frame
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x0, y0, x1, y1 = self.ref_rect
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cv2.rectangle(vis, (x0+w, y0), (x1+w, y1), (0, 255, 0), 2)
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for kp in self.ref_points:
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x, y = kp.pt
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cv2.circle(vis, (int(x+w), int(y)), 2, (0, 255, 255))
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match = self.match_frames()
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if match is not None:
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p0, p1, H = match
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for (x0, y0), (x1, y1) in zip(np.int32(p0), np.int32(p1)):
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cv2.line(vis, (x0+w, y0), (x1, y1), (0, 255, 0))
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x0, y0, x1, y1 = self.ref_rect
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corners = np.float32([[x0, y0], [x1, y0], [x1, y1], [x0, y1]])
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corners = np.int32( cv2.perspectiveTransform(corners.reshape(1, -1, 2), H) )
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cv2.polylines(vis, [corners], True, (255, 255, 255), 2)
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cv2.imshow('plane', vis)
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corners3d = np.hstack([corners0, np.zeros((4, 1), np.float32)])
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fx = 0.9
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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(corners3d, img_corners, 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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def on_rect(self, rect):
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x0, y0, x1, y1 = rect
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@ -123,11 +123,39 @@ class App:
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descs.append(desc)
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self.ref_points, self.ref_descs = points, np.uint8(descs)
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self.matcher.clear()
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self.matcher.add([self.ref_descs])
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def run(self):
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while True:
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ret, frame = self.cap.read()
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self.on_frame(frame)
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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 = np.fliplr(frame).copy()
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self.frame_points, self.frame_desc = self.detector.detectAndCompute(self.frame, None)
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if self.frame_desc is None: # detectAndCompute returns descs=None if not keypoints found
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self.frame_desc = []
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w, h = getsize(self.frame)
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vis = np.zeros((h, w*2, 3), np.uint8)
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vis[:h,:w] = self.frame
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if self.ref_frame is not None:
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vis[:h,w:] = self.ref_frame
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x0, y0, x1, y1 = self.ref_rect
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cv2.rectangle(vis, (x0+w, y0), (x1+w, y1), (0, 255, 0), 2)
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draw_keypoints(vis[:,w:], self.ref_points)
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draw_keypoints(vis, self.frame_points)
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if playing and self.ref_frame is not None:
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self.on_frame(vis)
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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)
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if ch == ord(' '):
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self.paused = not self.paused
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if ch == 27:
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break
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@ -136,5 +164,5 @@ if __name__ == '__main__':
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import sys
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try: video_src = sys.argv[1]
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except: video_src = '0'
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except: video_src = 0
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App(video_src).run()
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