def HSV(img_in, x, y):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
frameHSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
return {'BGR': frame[x, y], 'HSV': frameHSV[x, y]}
def get_cmass(img_in):
img = read_image(img_in)
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
mom = cv2.moments(img_gray)
mx = mom['m10'] / mom['m00']
my = mom['m01'] / mom['m00']
return (int(mx), int(my))
def HSV(img_in, x, y):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
frameHSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
return {'BGR': frame[x, y], 'HSV': frameHSV[x, y]}
def get_cmass(img_in):
img = read_image(img_in)
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
mom = cv2.moments(img_gray)
mx = mom['m10'] / mom['m00']
my = mom['m01'] / mom['m00']
return (int(mx), int(my))
def MinMaxAvgHSV(img_in, x1, y1, x2, y2, ignore_mask = None):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
frameHSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
MinHSV = np.array([255, 255, 255], dtype='int32')
MaxHSV = np.array([0, 0, 0], dtype='int32')
ignored = 0
not_ignored = 0
for j in range(x1, x2):
for i in range(y1, y2):
try:
if (frame[j, i] == ignore_mask).all():
ignored += 1
continue
except:
print j, i
print img_in.shape
not_ignored += 1
for k in [0, 1, 2]:
if frameHSV[j, i][k] < MinHSV[k]:
MinHSV[k] = frameHSV[j, i][k]
if frameHSV[j, i][k] > MaxHSV[k]:
MaxHSV[k] = frameHSV[j, i][k]
print 'ignored px.', ignored, 'not_ignored px.', not_ignored
AvgHSV = (MinHSV + MaxHSV) / 2
return (MinHSV.astype('uint8'), MaxHSV.astype('uint8'), AvgHSV.astype('uint8'))
def test_color():
color_ranges = []
for color in ['red', 'blue', 'yellow']:
img = read_image('../pure_markers/hand_3fingers_%s_frame300.png' % color)
color_rng = MinMaxHSV(img, 0, 0, img.shape[1], img.shape[0], ignore_mask = np.array([255, 255, 255]))
print color, color_rng
color_ranges.append(color_rng)
inters = ColorRangeIntersection(color_ranges[0], color_ranges[2])
volume = ColorRangeIntersectionVolume(inters)
print 'Intersection:', inters, 'Intersection volume:', volume
def test_color():
color_ranges = []
for color in ['red', 'blue', 'yellow']:
img = read_image('../pure_markers/hand_3fingers_%s_frame300.png' % color)
color_rng = MinMaxAvgHSV(img, 0, 0, img.shape[1], img.shape[0], ignore_mask = np.array([255, 255, 255]))
print color, color_rng
color_ranges.append(color_rng)
inters = ColorRangeIntersection(color_ranges[0], color_ranges[2])
volume = ColorRangeIntersectionVolume(inters)
print 'Intersection:', inters, 'Intersection volume:', volume
def MinMaxHSV(img_in, x1, y1, x2, y2, ignore_mask = None):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
frameHSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
MinHSV = [255, 255, 255]
MaxHSV = [0, 0, 0]
for i in range(x1, x2):
for j in range(y1, y2):
for k in [0, 1, 2]:
if ignore_mask != None and (frame[j, i] == ignore_mask).all():
continue
if frameHSV[j, i][k] < MinHSV[k]:
MinHSV[k] = frameHSV[j, i][k]
if frameHSV[j, i][k] > MaxHSV[k]:
MaxHSV[k] = frameHSV[j, i][k]
return (MinHSV, MaxHSV)
def MinMaxHSV(img_in, x1, y1, x2, y2, ignore_mask=None):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
frameHSV = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
MinHSV = [255, 255, 255]
MaxHSV = [0, 0, 0]
for i in range(x1, x2):
for j in range(y1, y2):
for k in [0, 1, 2]:
if ignore_mask != None and (frame[j, i] == ignore_mask).all():
continue
if frameHSV[j, i][k] < MinHSV[k]:
MinHSV[k] = frameHSV[j, i][k]
if frameHSV[j, i][k] > MaxHSV[k]:
MaxHSV[k] = frameHSV[j, i][k]
return (MinHSV, MaxHSV)
def GUIMinMaxHSV(img_in):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
cv2.namedWindow('wnd', 0)
cv2.setMouseCallback('wnd', on_mouse_event, 0)
cv2.imshow('wnd', frame)
points_selected = 0
points = []
while cv2.waitKey(100) != 32:
if len(points) == 2:
print MinMaxHSV(frame, points[0][0], points[0][1], points[1][0], points[1][1])
points = []
if mouse_events[cv2.EVENT_LBUTTONDOWN]:
points.append((mouse_x, mouse_y))
clear_events()
cv2.destroyWindow('wnd')
cv2.waitKey(1000)
def GUIMinMaxHSV(img_in):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
cv2.namedWindow('wnd', 0)
cv2.setMouseCallback('wnd', on_mouse_event, 0)
cv2.imshow('wnd', frame)
points_selected = 0
points = []
while cv2.waitKey(100) != 32:
if len(points) == 2:
print MinMaxAvgHSV(frame, points[0][0], points[0][1], points[1][0], points[1][1])
points = []
if mouse_events[cv2.EVENT_LBUTTONDOWN]:
points.append(np.array([mouse_x, mouse_y], dtype='uint16'))
clear_events_mouse()
cv2.destroyWindow('wnd')
cv2.waitKey(1000)
def generate_hist_files(fnames):
for fn in fnames:
pic_fn = fn[0:fn.rfind('.')]
h = calc_hue_hist(read_image(pic_fn))
cv2.normalize(h['data'], h['data'], 0, 255, cv2.NORM_MINMAX)
save_hist(h, fn)
def test_hue_hist():
img = read_image(FRAME_FILE)
h = calc_hue_hist(img)
loaded_h = load_hist(HIST_FILE)
return all(map(lambda x: x[0], loaded_h['data'] == h['data']))
def generate_hist_files(fnames):
for fn in fnames:
pic_fn = fn[0:fn.rfind('.')]
h = calc_hue_hist(read_image(pic_fn))
cv2.normalize(h['data'], h['data'], 0, 255, cv2.NORM_MINMAX)
save_hist(h, fn)
def test_hue_hist():
img = read_image(FRAME_FILE)
h = calc_hue_hist(img)
loaded_h = load_hist(HIST_FILE)
return all(map(lambda x: x[0], loaded_h['data'] == h['data']))
def GUICalibrateHSV(img_in, fname):
if type(img_in) == type(''):
frame = read_image(fname)
else:
frame = img_in
main_labels = [ '1) Draw a bounding box around next cube to zoom it in;',\
'2) In the zoomed area draw a contour around the cube, press \'Enter\';',\
'3) Select the color in the terminal:',\
' Type one character designating the color (r, g, b, c, m or y)',\
' and press \'Enter\';',\
'4) Then proceed with the next cube in the reopened image window;',\
'5) When all the cube types were selected, press \'Esc\' to exit.'\
]
labels = {\
'zoom1': main_labels,\
'zoom2': main_labels,\
'hsv_select_roi': [],\
'hsv': main_labels,\
}
disp_frame = frame.copy()
zoomed_frame = None
wnd_name = 'Calibrate Color for Cube detection'
cv2.namedWindow(wnd_name, 0)
cv2.setMouseCallback(wnd_name, on_mouse_event, 0)
points_selected = 0
points = []
state = 'zoom1'
draw_debug_messages(disp_frame, labels[state], font_size = 1.0)
cv2.imshow(wnd_name, disp_frame)
hsv_min = 255 * np.ones([3], dtype='uint8')
hsv_max = np.zeros([3], dtype='uint8')
color_strs = {\
'r': 'red',\
'g': 'green',\
'b': 'blue',\
'c': 'cyan',\
'm': 'magenta',\
'y': 'yellow',\
}
contour_selected = False
sub_state = None
def debug_state(state, points, events):
print 'State: %s, points: %s, mouse_events: %s' % (state, str(points), str(events))
while True:
#debug_state(state, points, mouse_events)
key = cv2.waitKey(5)
if key == 27:#Esc
break
key_events[key] = True
if key == ord('c') and state == 'hsv':
hsv_min = 255 * np.ones([3], dtype='uint8')
hsv_max = np.zeros([3], dtype='uint8')
points = []
elif state == 'hsv_select_roi':
if sub_state == 'cont_not_selected':
if mouse_events[cv2.EVENT_LBUTTONDOWN]:
sub_state = 'cont_select'
elif sub_state == 'cont_select':
zoomed_frame_contoured = zoomed_frame.copy()
draw_contour(zoomed_frame_contoured, points)
draw_debug_messages(zoomed_frame_contoured, labels[state], font_size = 1.0)
cv2.imshow(wnd_name, zoomed_frame_contoured)
if mouse_events[cv2.EVENT_LBUTTONUP]:
sub_state = 'cont_selected'
clear_events_mouse([cv2.EVENT_LBUTTONDOWN, cv2.EVENT_LBUTTONUP])
elif sub_state == 'cont_selected':
if key_events[10]:#Enter
clear_events_key([10])
#TODO: assert len(points) >= 2, otherwise switch to sub_state = 'cont_select',
#but also make new clicks be processed (points.append at the end of cycle)
state = 'hsv'
elif mouse_events[cv2.EVENT_LBUTTONDOWN]:
sub_state = 'cont_select'
elif mouse_events[cv2.EVENT_RBUTTONUP]:
points = []
elif state == 'hsv':
cont = np.array([points], dtype='int32')
#cont = np.array([[[1, 30]], [[30,1]], [[30, 30]], [[1, 1]]], dtype='int32')
mask = np.zeros_like(zoomed_frame)
cv2.drawContours(mask, cont, -1, SCALAR_WHITE, -1)#Draw contour with filled internals
selected_frame = np.bitwise_and(zoomed_frame, mask)
ignore_mask = np.array(SCALAR_BLACK[0:3], dtype=selected_frame.dtype)
(mi, ma, _) = MinMaxAvgHSV(selected_frame, 0, 0, selected_frame.shape[0], selected_frame.shape[1], ignore_mask)
for i in range(len(mi)):
if mi[i] < hsv_min[i]:
hsv_min[i] = mi[i]
if ma[i] > hsv_max[i]:
hsv_max[i] = ma[i]
cv2.destroyWindow(wnd_name)
while True:
try:
color = raw_input('colour [r, g, b, c, m, y]> ')
color = color_strs[color]
except KeyError, e:
print 'Invalid color: %s. Avaliable colors are: r, g, b, c, m, y. Retry.' % color
continue
break
f = file(fname, 'a+')
f.write('%s_hsv_min:\n' % color)
f.write(' h: %d\n' % hsv_min[0])
f.write(' s: %d\n' % hsv_min[1])
f.write(' v: %d\n' % hsv_min[2])
f.write('%s_hsv_max:\n' % color)
f.write(' h: %d\n' % hsv_max[0])
f.write(' s: %d\n' % hsv_max[1])
f.write(' v: %d\n' % hsv_max[2])
f.close()
print '%s written' % fname
cv2.imwrite('params/%s.png' % color, selected_frame)
print 'params/%s.png written' % color
cv2.namedWindow(wnd_name, 0)
cv2.setMouseCallback(wnd_name, on_mouse_event, 0)
disp_frame = frame.copy()
draw_debug_messages(disp_frame, labels[state], font_size = 1.0)
cv2.imshow(wnd_name, disp_frame)
state = 'zoom1'
clear_events_mouse([cv2.EVENT_LBUTTONDOWN, cv2.EVENT_LBUTTONUP])
hsv_min = 255 * np.ones([3], dtype='uint8')
hsv_max = np.zeros([3], dtype='uint8')
points = []
elif state == 'zoom1':
if len(points) == 1:
state = 'zoom2'
