def check_simmilarity(path1, path2):
src1 = cv.LoadImage(path1, cv.CV_LOAD_IMAGE_COLOR)
src2 = cv.LoadImage(path2, cv.CV_LOAD_IMAGE_COLOR)
hist1 = compute_histogram(src1)
hist2 = compute_histogram(src2)
sc = cv.CompareHist(hist1, hist2, cv.CV_COMP_BHATTACHARYYA)
return sc
def main():
interval = 1
capture = cv.CaptureFromCAM(0)
try:
last_frame = None
last_hist = None
last_filename = None
last_saved = False
while True:
frame = get_gray_frame(capture)
filename = get_file_name()
hist = get_frame_hist(frame)
change = False
if last_hist is not None:
method = cv.CV_COMP_CORREL
dist = cv.CompareHist(hist, last_hist, method)
change = dist <= 0.995
# print filename, last_filename, change, dist
if change:
if not last_saved:
cv.SaveImage(last_filename, last_frame)
cv.SaveImage(filename, frame)
last_saved = True
else:
last_saved = False
last_hist = hist
last_frame = frame
last_filename = filename
if change:
interval = 0.4
else:
interval = 0.8
time.sleep(interval)
except KeyboardInterrupt:
pass
def distance(self, current, other):
return cv.CompareHist(current, other, cv.CV_COMP_CHISQR)
def main():
BLACK_AND_WHITE = False
THRESHOLD = 0.48
BW_THRESHOLD = 0.4
os.chdir(sys.argv[1])
try:
os.mkdir(OUTPUT_DIR_NAME)
except:
pass
if len(sys.argv) > 2:
if sys.argv[2] == "bw":
BLACK_AND_WHITE = True
THRESHOLD = BW_THRESHOLD
print "##########"
print " B/W MODE"
print "##########"
tree = et.parse("project.xml")
movie = tree.getroot()
file_path = movie.attrib["path"]
cap = cv.CreateFileCapture(file_path)
if DEBUG:
cv.NamedWindow("win", cv.CV_WINDOW_AUTOSIZE)
cv.MoveWindow("win", 200, 200)
hist = None
prev_hist = None
prev_img = None
pixel_count = None
frame_counter = 0
last_frame_black = False
black_frame_start = -1
t = time.time()
while 1:
img_orig = cv.QueryFrame(cap)
if not img_orig: # eof
cv.SaveImage(OUTPUT_DIR_NAME + "\\%06d.png" % (frame_counter - 1),
prev_img)
"""movie.set("frames", str(frame_counter))
tree.write("project.xml")"""
break
img = cv.CreateImage(
(int(img_orig.width / 4), int(img_orig.height / 4)),
cv.IPL_DEPTH_8U, 3)
cv.Resize(img_orig, img, cv.CV_INTER_AREA)
if frame_counter == 0: # erster frame
cv.SaveImage(OUTPUT_DIR_NAME + "\\%06d.png" % (0), img)
pixel_count = img.width * img.height
prev_img = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_8U, 3)
cv.Zero(prev_img)
if DEBUG and frame_counter % 2 == 1:
cv.ShowImage("win", img)
img_hsv = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_8U, 3)
cv.CvtColor(img, img_hsv, cv.CV_BGR2HSV)
# #####################
# METHOD #1: find the number of pixels that have (significantly) changed since the last frame
diff = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_8U, 3)
cv.AbsDiff(img_hsv, prev_img, diff)
cv.Threshold(diff, diff, 10, 255, cv.CV_THRESH_BINARY)
d_color = 0
for i in range(1, 4):
cv.SetImageCOI(diff, i)
d_color += float(cv.CountNonZero(diff)) / float(pixel_count)
if not BLACK_AND_WHITE:
d_color = float(d_color / 3.0) # 0..1
# #####################
# METHOD #2: calculate the amount of change in the histograms
h_plane = cv.CreateMat(img.height, img.width, cv.CV_8UC1)
s_plane = cv.CreateMat(img.height, img.width, cv.CV_8UC1)
v_plane = cv.CreateMat(img.height, img.width, cv.CV_8UC1)
cv.Split(img_hsv, h_plane, s_plane, v_plane, None)
planes = [h_plane, s_plane, v_plane]
hist_size = [50, 50, 50]
hist_range = [[0, 360], [0, 255], [0, 255]]
if not hist:
hist = cv.CreateHist(hist_size, cv.CV_HIST_ARRAY, hist_range, 1)
cv.CalcHist([cv.GetImage(i) for i in planes], hist)
cv.NormalizeHist(hist, 1.0)
if not prev_hist:
prev_hist = cv.CreateHist(hist_size, cv.CV_HIST_ARRAY, hist_range,
1)
# wieso gibt es kein cv.CopyHist()?!
cv.CalcHist([cv.GetImage(i) for i in planes], prev_hist)
cv.NormalizeHist(prev_hist, 1.0)
continue
d_hist = cv.CompareHist(prev_hist, hist, cv.CV_COMP_INTERSECT)
# combine both methods to make a decision
if ((0.4 * d_color + 0.6 * (1 - d_hist))) >= THRESHOLD:
if DEBUG:
if frame_counter % 2 == 0:
cv.ShowImage("win", img)
winsound.PlaySound(soundfile,
winsound.SND_FILENAME | winsound.SND_ASYNC)
print "%.3f" % ((0.4 * d_color + 0.6 * (1 - d_hist))), "%.3f" % (
d_color), "%.3f" % (1 - d_hist), frame_counter
if DEBUG and DEBUG_INTERACTIVE:
if win32api.MessageBox(0, "cut?", "",
win32con.MB_YESNO) == 6: #yes
cv.SaveImage(
OUTPUT_DIR_NAME + "\\%06d.png" % (frame_counter), img)
else:
cv.SaveImage(OUTPUT_DIR_NAME + "\\%06d.png" % (frame_counter),
img)
cv.CalcHist([cv.GetImage(i) for i in planes], prev_hist)
cv.NormalizeHist(prev_hist, 1.0)
# #####################
# METHOD #3: detect series of (almost) black frames as an indicator for "fade to black"
average = cv.Avg(v_plane)[0]
if average <= 0.6:
if not last_frame_black: # possible the start
print "start", frame_counter
black_frame_start = frame_counter
last_frame_black = True
else:
if last_frame_black: # end of a series of black frames
cut_at = black_frame_start + int(
(frame_counter - black_frame_start) / 2)
print "end", frame_counter, "cut at", cut_at
img_black = cv.CreateImage(
(img_orig.width / 4, img_orig.height / 4), cv.IPL_DEPTH_8U,
3)
cv.Set(img_black, cv.RGB(0, 255, 0))
cv.SaveImage(OUTPUT_DIR_NAME + "\\%06d.png" % (cut_at),
img_black)
last_frame_black = False
cv.Copy(img_hsv, prev_img)
frame_counter += 1
if DEBUG:
if cv.WaitKey(1) == 27:
break
if DEBUG:
cv.DestroyWindow("win")
print "%.2f min" % ((time.time() - t) / 60)
#raw_input("- done -")
return
#cv.Or(avg_noise, scratch, avg_noise)
#
#cv.Sub(back_proj_img2, avg_noise, back_proj_img2)
#cv.Sub(scratch,, back_proj_img2)
cv.ShowImage("final", scratch)
#cv.Sub(scratch, avg_noise, scratch2)
#cv.And(scratch, back_proj_img2, scratch2)
#cv.SubRS(scratch2, 255, scratch)
#cv.ShowImage("final", back_proj_img)
print cv.CompareHist(hist1, hist2, cv.CV_COMP_BHATTACHARYYA)
#making a mask
#mask = cv.CreateImage(cv.GetSize(back_proj_img2), 8, 1)
#cv.SubRS(back_proj_img2, 255, back_proj_img2)
#cv.SubRS(back_proj_img, 255, back_proj_img, mask=back_proj_img2)
#cv.SubRS(back_proj_img, 255, back_proj_img)
#cv.MorphologyEx(back_proj_img,back_proj_img, None, None, cv.CV_MOP_OPEN, 8)
#cv.MorphologyEx(back_proj_img,back_proj_img, None, None, cv.CV_MOP_CLOSE, 8)
#cv.ShowImage("back_projection", back_proj_img2)
#cv.WaitKey(0)
cv.Scale(back_proj_img, back_proj_img, 1/255.0)
print "here's the sum :", cv.Sum(scratch2)
planes = [r_plane, g_plane, b_plane]
histogram = cv.CreateHist([256 / 8, 256 / 8, 256 / 8], cv.CV_HIST_ARRAY,
[(0, 255), (0, 255), (0, 255)], 1)
cv.ClearHist(histogram)
cv.CalcHist([cv.GetImage(i) for i in planes],
histogram,
accumulate=0,
mask=maskArray)
cv.NormalizeHist(histogram, 1.0)
# Test it against each of the learnt histograms in turn
print objectName
for otherObjectName in learntHistograms.keys():
print " " + otherObjectName + ": " \
+ str( cv.CompareHist( histogram, learntHistograms[ otherObjectName ], cv.CV_COMP_INTERSECT ) )
#learntHistograms[ otherObjectName ], cv.CV_COMP_INTERSECT ) )
#if objectName == "Sellotape":
# savedHistogram = histogram
#z = np.array( r_plane )
#x = np.array( g_plane )
#y = np.array( b_plane )
#print z[ (z > 0) & (x > 0) & (y > 0) & (maskArray == 255) ].size
#for i in range( 8 ):
#for j in range( 8 ):
#a = ""
#for k in range( 8 ):
#a += str( cv.QueryHistValue_3D( histogram, i, j, k ) )
