def show_recognize(clf, img, rects):
red = [0,0,0xff]
if len(rects) == 0:
return
for i,rect in enumerate(rects):
img2 = op.get_subimage(img, rect[0], rect[1])
cv2.imshow(str(i),img2)
res = model.recognize_number(clf, img2)
cv2.putText(img, str(int(res)), rect[0], cv2.FONT_HERSHEY_SIMPLEX,0.8, red, thickness = 2)
def show_recognize(clf, img, rects):
red = [0, 0, 0xff]
if len(rects) == 0:
return
for i, rect in enumerate(rects):
img2 = op.get_subimage(img, rect[0], rect[1])
cv2.imshow(str(i), img2)
res = model.recognize_number(clf, img2)
cv2.putText(img,
str(int(res)),
rect[0],
cv2.FONT_HERSHEY_SIMPLEX,
0.8,
red,
thickness=2)
def on_mouse(event, x, y, flags, param):
global point_s
global img
global rects
green = [0x0, 0xFF, 0x0]
read = [0x0, 0x0, 0xFF]
if event == cv2.cv.CV_EVENT_LBUTTONDOWN:
img_cpy = img.copy() # copy image to draw rectangle
point_s = (x, y)
cv2.circle(img_cpy, point_s, 1, green)
cv2.imshow(win_name, img_cpy)
elif event == cv2.cv.CV_EVENT_RBUTTONDOWN:
print 'cancel last region'
if len(rects) != 0:
rects.pop()
target_imgs.pop()
elif event == cv2.cv.CV_EVENT_MOUSEMOVE and (
flags & cv2.cv.CV_EVENT_FLAG_LBUTTON):
img_cpy = img.copy() # copy image to draw rectangle
point_e = (x, y)
if point_s != point_e:
cv2.circle(img_cpy, point_e, 2, green) # draw point
cv2.rectangle(img_cpy, point_s, point_e, read)
cv2.imshow(win_name, img_cpy)
elif event == cv2.cv.CV_EVENT_LBUTTONUP:
point_e = (x, y)
img_cpy = img.copy() # copy image to draw rectangle
if point_s != point_e:
cv2.circle(img_cpy, point_e, 2, green)
cv2.rectangle(img_cpy, point_s, point_e, read)
cv2.imshow(win_name, img_cpy)
img2 = op.get_subimage(img, point_s, point_e)
# img2 = cv2.resize(img2,(26,26))
# cv2.imwrite('heihei.jpg',img2)
rects.append((point_s, point_e))
target_imgs.append(img2)
print 'add region', point_s, point_e
def on_mouse(event, x, y, flags, param):
global point_s
global img
global rects
green = [0x0,0xFF,0x0]
read = [0x0,0x0,0xFF]
if event == cv2.cv.CV_EVENT_LBUTTONDOWN:
img_cpy = img.copy() # copy image to draw rectangle
point_s = (x,y)
cv2.circle(img_cpy, point_s, 1, green)
cv2.imshow(win_name,img_cpy)
elif event == cv2.cv.CV_EVENT_RBUTTONDOWN:
print 'cancel last region'
if len(rects) != 0:
rects.pop()
target_imgs.pop()
elif event == cv2.cv.CV_EVENT_MOUSEMOVE and (flags & cv2.cv.CV_EVENT_FLAG_LBUTTON):
img_cpy = img.copy() # copy image to draw rectangle
point_e = (x,y)
if point_s != point_e:
cv2.circle(img_cpy, point_e, 2, green) # draw point
cv2.rectangle(img_cpy, point_s, point_e, read)
cv2.imshow(win_name,img_cpy)
elif event == cv2.cv.CV_EVENT_LBUTTONUP:
point_e = (x,y)
img_cpy = img.copy() # copy image to draw rectangle
if point_s != point_e:
cv2.circle(img_cpy, point_e, 2, green)
cv2.rectangle(img_cpy, point_s, point_e, read)
cv2.imshow(win_name,img_cpy)
img2 = op.get_subimage(img, point_s, point_e)
# img2 = cv2.resize(img2,(26,26))
# cv2.imwrite('heihei.jpg',img2)
rects.append((point_s,point_e))
target_imgs.append(img2)
print 'add region', point_s, point_e
def get_score_info(video):
global step
score_frames = []
twenty_four_frames = []
camera_change_frames = []
score_a, score_b = 0, 0 # score of both team
last_sec = 0 # 24 second board
# last_frame = None
pos = 0 # frame position
video.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, pos)
clf = model.load_classifier()
while (video.isOpened()):
if pos % step == 0:
ret, frame = video.red()
else:
ret = video.grab()
if not ret:
break
# skip each step steps
if pos % step != 0:
pos += 1
continue
# if camera change
if pos != 0 and hist.camera_change(last_frame, frame):
camera_change_frames.append(pos)
print 'camera change', pos
last_frame = frame
if op.has_score_board(frame, target_imgs[0], rects[0]):
# score a
img = op.get_subimage(frame, rects[1][0], rects[1][1])
num = model.recognize_number(clf, img)
# print 'a ', num
if score_two_or_three(num, score_a):
score_frames.append(pos)
print 'a from', score_a, 'to', num, pos
if not noise(num, score_a):
score_a = num
# score b
img = op.get_subimage(frame, rects[2][0], rects[2][1])
num = model.recognize_number(clf, img)
# print 'b ', num
if score_two_or_three(num, score_b):
score_frames.append(pos)
print 'b from', score_b, 'to', num, pos
if not noise(num, score_b):
score_b = num
# 24 second board
img = op.get_subimage(frame, rects[3][0], rects[3][1])
sec = model.recognize_number(clf, img)
if last_sec != 24 and sec == 24:
print 'twenty four', pos
twenty_four_frames.append(pos)
last_sec = sec
pos += 1
# print pos
print score_frames, twenty_four_frames, camera_change_frames
return score_frames, twenty_four_frames, camera_change_frames
def get_score_info(video):
global step
score_frames = []
twenty_four_frames = []
camera_change_frames = []
score_a, score_b = 0,0 # score of both team
last_sec = 0 # 24 second board
# last_frame = None
pos = 0 # frame position
video.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, pos)
clf = model.load_classifier()
while(video.isOpened()):
if pos % step == 0:
ret, frame = video.red()
else:
ret = video.grab()
if not ret:
break
# skip each step steps
if pos % step != 0:
pos += 1
continue
# if camera change
if pos != 0 and hist.camera_change(last_frame, frame):
camera_change_frames.append(pos)
print 'camera change', pos
last_frame = frame
if op.has_score_board(frame, target_imgs[0], rects[0]):
# score a
img = op.get_subimage(frame, rects[1][0], rects[1][1])
num = model.recognize_number(clf, img)
# print 'a ', num
if score_two_or_three(num,score_a):
score_frames.append(pos)
print 'a from',score_a,'to',num, pos
if not noise(num, score_a):
score_a = num
# score b
img = op.get_subimage(frame, rects[2][0], rects[2][1])
num = model.recognize_number(clf, img)
# print 'b ', num
if score_two_or_three(num,score_b):
score_frames.append(pos)
print 'b from',score_b,'to', num, pos
if not noise(num, score_b):
score_b = num
# 24 second board
img = op.get_subimage(frame, rects[3][0], rects[3][1])
sec = model.recognize_number(clf, img)
if last_sec != 24 and sec == 24:
print 'twenty four',pos
twenty_four_frames.append(pos)
last_sec = sec
pos += 1
# print pos
print score_frames, twenty_four_frames, camera_change_frames
return score_frames,twenty_four_frames,camera_change_frames
