def circularity(paths, dest):
paths = pickle.load(open(paths))
ims = [draw(smooth) for raw,smooth in paths]
sizes = np.array([[x.shape[1], x.shape[0]] for x in ims])
w = sizes[:,0].max()
h = sizes[:,1].sum()
out = np.zeros((h,w,3), np.uint8)
cury = 0
for im in ims:
out[cury:cury+im.shape[0],:im.shape[1]] = im
cury += im.shape[0]
np2image(out, dest)
def contours(src, dst):
acc = []
video = None
vfr = None
BLUR = getRule("blur", src)
DILATION = getRule("dilation", src)
THRESH = getRule("threshold", src)
REVERSED = getRule("reversed", src)
MERGE = getRule("merge", src)
CROP = getRule("crop", src)
merge = []
for idx,fr in enumerate(VideoReader(src)):
if CROP > 0:
fr = fr[CROP:-CROP,CROP:-CROP]
if len(merge) >= MERGE:
merge.pop(0)
merge.append(fr.mean(axis=2).astype(int))
fr = (array(merge).sum(axis=0) / len(merge)).astype(uint8)
if REVERSED:
fr = 255 - fr
if BLUR > 0:
cv2.blur(fr, (BLUR, BLUR), fr)
fr = 255*(fr>THRESH).astype(uint8)
fr = cv2.dilate(fr, None, iterations=DILATION)
if idx == 0:
video = VideoWriter(dst.replace('.pkl', '.avi'))
vfr = zeros((fr.shape[0],fr.shape[1],3), uint8)
np2image(fr, dst.replace('.pkl', '.png'))
vfr[:] = fr.reshape((fr.shape[0],fr.shape[1],-1))
video.write(vfr)
contours, hierarchy = cv2.findContours(fr, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
acc.append(contours)
pickle.dump(acc, open(dst, 'w'))
def first(src, dst):
vf = VideoReader(src)
fr = vf.next()
np2image(fr, dst)
