def check_for_card(self):
found = False
base_corr = 0
self.grab_frame()
# if the user didn't set the background, get the first frame and consider it the background
if self.background is None:
print "Updating background on the account of it being NOne"
self.update_background()
history_diff = self.calc_biggest_diff()
# Detect movement
if history_diff > 10:
self.has_moved = True
# No movement now, but there was before
elif self.has_moved == True:
base_corr = self.calc_background_similarity()
# Looking at the background, false alarm
# set the frame as the new background, this helps with lightning change
if base_corr >= 0.75:
#self.update_background()
self.has_moved = False
else:
# background and current frame are < 25% similar
corners = detect_card(self.last_frame_gray, self.background_gray)
if corners is not None:
self.snapshot = get_card(self.last_frame_gray, corners)
self.snapshot = flip_image(self.snapshot)
found = True
self.has_moved = False
else:
self.has_moved = False
self.display_background()
self.display_live("%.4f [0-10 stable, >10 unstable] | %.4f [>0.75 is background, <0.75 contains foreground]" % (history_diff, base_corr))
if found is True:
return clone_image(self.snapshot)
return None
def watch_for_card(camera):
has_moved = False
been_to_base = False
global captures
global font
captures = []
font = cv.InitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 1.0, 1.0)
img = cv.QueryFrame(camera)
size = cv.GetSize(img)
n_pixels = size[0] * size[1]
grey = cv.CreateImage(size, 8, 1)
recent_frames = [cv.CloneImage(grey)]
base = cv.CloneImage(grey)
cv.CvtColor(img, base, cv.CV_RGB2GRAY)
# cv.ShowImage('card', base)
tmp = cv.CloneImage(grey)
while True:
img = cv.QueryFrame(camera)
cv.CvtColor(img, grey, cv.CV_RGB2GRAY)
biggest_diff = max(sum_squared(grey, frame) / n_pixels for frame in recent_frames)
# display the cam view
cv.PutText(img, "%s" % biggest_diff, (1, 24), font, (255, 255, 255))
cv.ShowImage('win', img)
recent_frames.append(cv.CloneImage(grey))
if len(recent_frames) > 3:
del recent_frames[0]
# check for keystroke
c = cv.WaitKey(10)
# if there was a keystroke, reset the last capture
if c == 27:
return captures
elif c == 32:
has_moved = True
been_to_base = True
elif c == 114:
base = cv.CloneImage(grey)
# if we're stable-ish
if biggest_diff < 10:
# if we're similar to base, update base
# else, check for card
# base_diff = max(sum_squared(base, frame) / n_pixels for frame in recent_frames)
base_corr = 0
try:
base_corr = min(ccoeff_normed(base, frame) for frame in recent_frames)
except:
print ("Unable to calculate the base_corr")
pass
# cv.ShowImage('debug', base)
"""for i, frame in enumerate(recent_frames):
tmp = cv.CloneImage(base)
cv.Sub(base, frame, tmp)
cv.Pow(tmp, tmp, 2.0)
cv.PutText(tmp, "%s" % (i+1), (1,24), font, (255, 255, 255))
#my_diff = sum_squared(base, frame) / n_pixels
my_diff = ccoeff_normed(base, frame) #score(base, frame, cv.CV_TM_CCOEFF_NORMED)
cv.PutText(tmp, "%s" % my_diff, (40, 24), font, (255, 255, 255))
cv.ShowImage('dbg%s' % (i+1), tmp)"""
# print "stable. corr = %s. moved = %s. been_to_base = %s" % (base_corr, has_moved, been_to_base)
if base_corr > 0.75 and not been_to_base:
base = cv.CloneImage(grey)
# cv.ShowImage('debug', base)
has_moved = False
been_to_base = True
print "STATE: been to base. waiting for move"
elif has_moved and been_to_base:
corners = detect_card(grey, base)
if corners is not None:
card = get_card(grey, corners)
cv.Flip(card, card, -1)
captures.append(card)
update_windows()
# cv.ShowImage('card', card)
has_moved = False
been_to_base = False
print "STATE: detected. waiting for go to base"
else:
if not has_moved:
print "STATE: has moved. waiting for stable"
has_moved = True
def watch_for_card(camera):
has_moved = False
been_to_base = False
global captures
global font
captures = []
font = cv.InitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 1.0, 1.0)
img = cv.QueryFrame(camera)
size = cv.GetSize(img)
n_pixels = size[0] * size[1]
grey = cv.CreateImage(size, 8, 1)
recent_frames = [cv.CloneImage(grey)]
base = cv.CloneImage(grey)
cv.CvtColor(img, base, cv.CV_RGB2GRAY)
#cv.ShowImage('card', base)
tmp = cv.CloneImage(grey)
while True:
img = cv.QueryFrame(camera)
cv.CvtColor(img, grey, cv.CV_RGB2GRAY)
biggest_diff = max(
sum_squared(grey, frame) / n_pixels for frame in recent_frames)
#display the cam view
cv.PutText(img, "%s" % biggest_diff, (1, 24), font, (255, 255, 255))
cv.ShowImage('win', img)
recent_frames.append(cv.CloneImage(grey))
if len(recent_frames) > 3:
del recent_frames[0]
#check for keystroke
c = cv.WaitKey(10)
#if there was a keystroke, reset the last capture
if c == 27:
return captures
elif c == 32:
has_moved = True
been_to_base = True
elif c == 114:
base = cv.CloneImage(grey)
#if we're stable-ish
if biggest_diff < 10:
#if we're similar to base, update base
#else, check for card
#base_diff = max(sum_squared(base, frame) / n_pixels for frame in recent_frames)
base_corr = min(
ccoeff_normed(base, frame) for frame in recent_frames)
#cv.ShowImage('debug', base)
"""for i, frame in enumerate(recent_frames):
tmp = cv.CloneImage(base)
cv.Sub(base, frame, tmp)
cv.Pow(tmp, tmp, 2.0)
cv.PutText(tmp, "%s" % (i+1), (1,24), font, (255, 255, 255))
#my_diff = sum_squared(base, frame) / n_pixels
my_diff = ccoeff_normed(base, frame) #score(base, frame, cv.CV_TM_CCOEFF_NORMED)
cv.PutText(tmp, "%s" % my_diff, (40, 24), font, (255, 255, 255))
cv.ShowImage('dbg%s' % (i+1), tmp)"""
#print "stable. corr = %s. moved = %s. been_to_base = %s" % (base_corr, has_moved, been_to_base)
if base_corr > 0.75 and not been_to_base:
base = cv.CloneImage(grey)
# cv.ShowImage('debug', base)
has_moved = False
been_to_base = True
print "STATE: been to base. waiting for move"
elif has_moved and been_to_base:
corners = detect_card(grey, base)
if corners is not None:
card = get_card(grey, corners)
cv.Flip(card, card, -1)
captures.append(card)
update_windows()
#cv.ShowImage('card', card)
has_moved = False
been_to_base = False
print "STATE: detected. waiting for go to base"
else:
if not has_moved:
print "STATE: has moved. waiting for stable"
has_moved = True
import numpy as np
from detect_card import detect_card
def multiple_crop(photopath):
# Now let's use the detector as you would in a normal application. First we
# will load it from disk.
detector = dlib.simple_object_detector("detector.svm")
img = io.imread(photopath)
dets = detector(img)
detected_rectangles= []
for k, d in enumerate(dets):
detected_rectangles.append([d.left(),d.top(),d.right(),d.bottom()])
# print(detected_rectangles)
cropped_vector=crop_cards(img, detected_rectangles)
# print(cropped_vector)
return cropped_vector
def crop_cards(img, rectanglelist):
cropped_img=[]
for i in rectanglelist:
single_crop=img[i[0]:i[2], i[1]:i[3]]
cropped_img.append(single_crop)
return cropped_img
crops=multiple_crop("Training/7.jpg")
gray=cv2.cvtColor(crops[0],0)
base= cv2.imread("base.jpg",0)
detect_card(gray,base)
