def detect_dots_with_box(data, pixel_threshold, opts, x1, y1, x2, y2):
"""
Extract the dots from data contained in a single frame. The detected dots are then filtered based on
the min/max dot size, circularity, etc.
"""
min_min, max_max = 2, opts['max_dot_size'] * 2
if isinstance(pixel_threshold, tuple) and len(pixel_threshold) == 3:
dots = ISCV.detect_bright_dots(data, pixel_threshold[0],
pixel_threshold[1], pixel_threshold[2],
x1, y1, x2, y2)
else:
dots = ISCV.detect_bright_dots(data, pixel_threshold, pixel_threshold,
pixel_threshold, x1, y1, x2, y2)
min_ds, max_ds, circ = opts['min_dot_size']**4, opts[
'max_dot_size']**4, opts['circularity_threshold']**2
filtered_dots = [
dot for dot in dots
if (dot.x1 - dot.x0 + dot.y1 -
dot.y0) > min_min and (dot.x1 - dot.x0 + dot.y1 - dot.y0) < max_max
and (dot.sxx * dot.syy) > min_ds and (dot.sxx * dot.syy) < max_ds
and dot.sxx < circ * dot.syy and dot.syy < circ * dot.sxx
]
height, width, chans = data.shape
psc = np.array([2.0 / width, -2.0 / width], dtype=np.float32)
pof = np.array([-1.0, height / float(width)], dtype=np.float32)
dotScreenCoords = np.array([[dot.sx, dot.sy] for dot in filtered_dots],
dtype=np.float32).reshape(-1, 2) * psc + pof
return filtered_dots, dotScreenCoords
def setFrame(newFrame):
global frame, view, allSkels, points, joints, bones
frame = newFrame
for Gs3, Ls3, skelDict3, animData3, skel3 in allSkels:
dofs3 = animData3[frame % len(animData3)]
Gs3 = ASFReader.pose_skeleton(Gs3, Ls3, skelDict3['jointParents'],
skelDict3['jointDofs'],
skelDict3['dofSplits'], dofs3)
skel3.vertices[:] = Gs3[:, :, 3]
global md, img, g_detectingDots, g_readingMovie
if g_readingMovie and md is not None:
try:
MovieReader.readFrame(md, seekFrame=(frame - videoFrameOffset) / 4)
except:
frame = videoFrameOffset
MovieReader.readFrame(md, seekFrame=(frame - videoFrameOffset) / 4)
if g_detectingDots:
ret = ISCV.detect_bright_dots(img, 254, 200, 190)
good = [
r for r in ret
if min(r.sxx, r.syy) > 0.1 and min(r.sxx, r.syy) < 100.0
] # and r.sxy*r.sxy<=0.01*r.sxx*r.syy]
print len(good), 'good points'
for r in good:
#print r.sx,r.sy,r.sxx,r.sxy,r.syy
img[int(r.sy - 5):int(r.sy + 5),
int(r.sx - 5):int(r.sx + 5), :] = [0, 255, 0]
view.refreshImageData()
global animJoints, stablePointsGroups, displayFrames, groupRepresentatives
pfr = np.searchsorted(goodFrames, frame)
points.vertices = displayFrames[pfr % len(displayFrames)]
if animJoints is not None:
joints.vertices[:] = animJoints[pfr % len(animJoints)]
bones.vertices[::2] = joints.vertices
bones.vertices[1::2] = points.vertices[
groupRepresentatives[stablePointsGroups]]
view.updateGL()