"""
Press 's' to take a picture or 'l' to load one and start real-time
"""
import cv2
import numpy as np
from cam import MyCam
from fmatch import draw_match
MIN_MATCH_COUNT = 10
# Initiate SIFT detector
orb = cv2.ORB()
cam = MyCam()
cam.size = (640, 480)
img1 = img1 = cv2.imread('box.png', 0)
cv2.imshow('source', img1)
while True:
img2 = cv2.flip(cv2.cvtColor(cam.read(), cv2.COLOR_BGR2GRAY), 1)
k = cv2.waitKey(5)
if k == ord('s'):
img1 = img2.copy()
cv2.imwrite('campic.png', img1)
elif k == 27:
break
# find the keypoints and descriptors with ORB
if k is not None:
Press 's' to take a picture or 'l' to load one and start real-time
"""
import cv2
import numpy as np
from cam import MyCam
from fmatch import draw_match
MIN_MATCH_COUNT = 10
# Initiate SIFT detector
sift = cv2.SIFT()
cam = MyCam()
cam.size = (640, 480)
img1 = img1 = cv2.imread('box.png', 0)
cv2.imshow('source', img1)
while True:
img2 = cv2.flip(cv2.cvtColor(cam.read(), cv2.COLOR_BGR2GRAY), 1)
k = cv2.waitKey(5)
if k == ord('s'):
img1 = img2.copy()
cv2.imwrite('campic.png', img1)
elif k== 27:
break
# find the keypoints and descriptors with SIFT
import cv2
import numpy as np
from cam import MyCam
from fmatch import draw_match
print __doc__
MIN_MATCH_COUNT = 10
# Initiate SIFT detector
sift = cv2.SIFT()
cam = MyCam()
cam.size = (640, 480)#(160, 120)
img1 = cv2.imread('box.png', 0)
cv2.imshow('source', img1)
if img1.shape[0] * img1.shape[1] > cam.size[0] * cam.size[1]:
img1 = cv2.resize(img1, cam.size)
kp1, des1 = sift.detectAndCompute(img1,None)
while True:
img2 = cv2.cvtColor(cam.read(), cv2.COLOR_BGR2GRAY)
k = cv2.waitKey(5)
if k == ord('s'):
img1 = img2.copy()
kp1, des1 = sift.detectAndCompute(img1,None)
"""
Press 's' to take a picture or 'l' to load one and start real-time
"""
import cv2
import numpy as np
from cam import MyCam
from fmatch import draw_match
MIN_MATCH_COUNT = 10
# Initiate SIFT detector
sift = cv2.SIFT()
cam = MyCam()
cam.size = (640, 480) #(160, 120)
img1 = cv2.imread('box.png', 0)
cv2.imshow('source', img1)
if img1.shape[0] * img1.shape[1] > cam.size[0] * cam.size[1]:
img1 = cv2.resize(img1, cam.size)
kp1, des1 = sift.detectAndCompute(img1, None)
while True:
img2 = cv2.cvtColor(cam.read(), cv2.COLOR_BGR2GRAY)
k = cv2.waitKey(5)
if k == ord('s'):
img1 = img2.copy()
kp1, des1 = sift.detectAndCompute(img1, None)
def test_feature_matching_realtime(detetor=cv2.ORB()):
from cam import MyCam
"""
Press 's' to take a picture or 'l' to load one and start real-time
"""
MIN_MATCH_COUNT = 10
cam = MyCam()
cam.size = (640, 480)
img1 = img1 = cv2.imread('box.png', 0)
cv2.imshow('source', img1)
while True:
img2 = cv2.flip(cv2.cvtColor(cam.read(), cv2.COLOR_BGR2GRAY), 1)
k = cv2.waitKey(5)
if k == ord('s'):
img1 = img2.copy()
cv2.imwrite('campic.png', img1)
elif k== 27:
break
# find the keypoints and descriptors with ORB
if k is not None:
cv2.destroyWindow('preview')
kp1, des1 = detetor.detectAndCompute(img1,None)
kp2, des2 = detetor.detectAndCompute(img2,None)
# If nothing match then continue
if des2 is None:
img3 = img3 = draw_match(img1,kp1,img2,kp2,[])
continue
des1 = des1.astype(np.uint8, copy=False) # Fix the data type
des2 = des2.astype(np.uint8, copy=False)
# Now match describers
bf = cv2.BFMatcher(cv2.NORM_HAMMING)
# matches = bf.match(des1,des2)
matches = bf.knnMatch(des1,des2, k=2)
# m = matches[0][0]
# p1, p2 = np.float32(kp1[m.queryIdx].pt), np.float32(kp2[m.trainIdx].pt)
# print m.distance, p1, p2
# Apply ratio test
good = []
try:
for m,n in matches:
if m.distance < 0.7*n.distance:
good.append(m)
except ValueError:
good = []
if len(good)>MIN_MATCH_COUNT:
src_pts = np.float32([ kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
dst_pts = np.float32([ kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
matchesMask = mask.ravel().tolist()
h,w = img1.shape
pts = np.float32([ [0,0],[0,h-1],[w-1,h-1],[w-1,0] ]).reshape(-1,1,2)
dst = cv2.perspectiveTransform(pts,M)
cv2.polylines(img2,[np.int32(dst)], True, (0,0,255) ,3)
else:
# print "Not enough matches are found - %d/%d" % (len(good),MIN_MATCH_COUNT)
matchesMask = None
good = []
img3 = draw_match(img1,kp1,img2,kp2,good, matchesMask=matchesMask)
cv2.imshow('matches', img3)
print 'press any key to continue'
