def dataset_viz(show_frustum=False):
sunrgbd = sunrgbd_object(data_dir)
idxs = np.array(range(1, len(sunrgbd) + 1))
np.random.shuffle(idxs)
for idx in range(len(sunrgbd)):
data_idx = idxs[idx]
print('--------------------', data_idx)
pc = sunrgbd.get_depth(data_idx)
print(pc.shape)
# Project points to image
calib = sunrgbd.get_calibration(data_idx)
uv, d = calib.project_upright_depth_to_image(pc[:, 0:3])
print(uv)
print(d)
raw_input()
import matplotlib.pyplot as plt
cmap = plt.cm.get_cmap('hsv', 256)
cmap = np.array([cmap(i) for i in range(256)])[:, :3] * 255
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i in range(uv.shape[0]):
depth = d[i]
color = cmap[int(120.0 / depth), :]
cv2.circle(img, (int(np.round(uv[i, 0])), int(np.round(uv[i, 1]))),
2,
color=tuple(color),
thickness=-1)
Image.fromarray(img).show()
raw_input()
# Load box labels
objects = sunrgbd.get_label_objects(data_idx)
print(objects)
raw_input()
# Draw 2D boxes on image
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i, obj in enumerate(objects):
cv2.rectangle(img, (int(obj.xmin), int(obj.ymin)),
(int(obj.xmax), int(obj.ymax)), (0, 255, 0), 2)
cv2.putText(img, '%d %s' % (i, obj.classname),
(max(int(obj.xmin), 15), max(int(obj.ymin), 15)),
cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 2)
Image.fromarray(img).show()
raw_input()
# Draw 3D boxes on depth points
box3d = []
ori3d = []
for obj in objects:
corners_3d_image, corners_3d = utils.compute_box_3d(obj, calib)
ori_3d_image, ori_3d = utils.compute_orientation_3d(obj, calib)
print('Corners 3D: ', corners_3d)
box3d.append(corners_3d)
ori3d.append(ori_3d)
raw_input()
bgcolor = (0, 0, 0)
fig = mlab.figure(figure=None,
bgcolor=bgcolor,
fgcolor=None,
engine=None,
size=(1600, 1000))
mlab.points3d(pc[:, 0],
pc[:, 1],
pc[:, 2],
pc[:, 2],
mode='point',
colormap='gnuplot',
figure=fig)
mlab.points3d(0,
0,
0,
color=(1, 1, 1),
mode='sphere',
scale_factor=0.2)
draw_gt_boxes3d(box3d, fig=fig)
for i in range(len(ori3d)):
ori_3d = ori3d[i]
x1, y1, z1 = ori_3d[0, :]
x2, y2, z2 = ori_3d[1, :]
mlab.plot3d([x1, x2], [y1, y2], [z1, z2],
color=(0.5, 0.5, 0.5),
tube_radius=None,
line_width=1,
figure=fig)
mlab.orientation_axes()
for i, obj in enumerate(objects):
print('Orientation: ', i,
np.arctan2(obj.orientation[1], obj.orientation[0]))
print('Dimension: ', i, obj.l, obj.w, obj.h)
raw_input()
if show_frustum:
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i, obj in enumerate(objects):
box2d_fov_inds = (uv[:, 0] < obj.xmax) & (
uv[:, 0] >= obj.xmin) & (uv[:, 1] <
obj.ymax) & (uv[:, 1] >= obj.ymin)
box2d_fov_pc = pc[box2d_fov_inds, :]
img2 = np.copy(img)
cv2.rectangle(img2, (int(obj.xmin), int(obj.ymin)),
(int(obj.xmax), int(obj.ymax)), (0, 255, 0), 2)
cv2.putText(img2, '%d %s' % (i, obj.classname),
(max(int(obj.xmin), 15), max(int(obj.ymin), 15)),
cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 0, 0), 2)
Image.fromarray(img2).show()
fig = mlab.figure(figure=None,
bgcolor=bgcolor,
fgcolor=None,
engine=None,
size=(1000, 1000))
mlab.points3d(box2d_fov_pc[:, 0],
box2d_fov_pc[:, 1],
box2d_fov_pc[:, 2],
box2d_fov_pc[:, 2],
mode='point',
colormap='gnuplot',
figure=fig)
raw_input()
def dataset_viz(show_frustum=False):
sunrgbd = sunrgbd_object(data_dir)
idxs = np.array(range(1,len(sunrgbd)+1))
np.random.shuffle(idxs)
for idx in range(len(sunrgbd)):
data_idx = idxs[idx]
print('--------------------', data_idx)
pc = sunrgbd.get_depth(data_idx)
print(pc.shape)
# Project points to image
calib = sunrgbd.get_calibration(data_idx)
uv,d = calib.project_upright_depth_to_image(pc[:,0:3])
print(uv)
print(d)
raw_input()
import matplotlib.pyplot as plt
cmap = plt.cm.get_cmap('hsv', 256)
cmap = np.array([cmap(i) for i in range(256)])[:,:3]*255
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i in range(uv.shape[0]):
depth = d[i]
color = cmap[int(120.0/depth),:]
cv2.circle(img, (int(np.round(uv[i,0])), int(np.round(uv[i,1]))), 2, color=tuple(color), thickness=-1)
Image.fromarray(img).show()
raw_input()
# Load box labels
objects = sunrgbd.get_label_objects(data_idx)
print(objects)
raw_input()
# Draw 2D boxes on image
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i,obj in enumerate(objects):
cv2.rectangle(img, (int(obj.xmin),int(obj.ymin)), (int(obj.xmax),int(obj.ymax)), (0,255,0), 2)
cv2.putText(img, '%d %s'%(i,obj.classname), (max(int(obj.xmin),15), max(int(obj.ymin),15)), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,0,0), 2)
Image.fromarray(img).show()
raw_input()
# Draw 3D boxes on depth points
box3d = []
ori3d = []
for obj in objects:
corners_3d_image, corners_3d = utils.compute_box_3d(obj, calib)
ori_3d_image, ori_3d = utils.compute_orientation_3d(obj, calib)
print('Corners 3D: ', corners_3d)
box3d.append(corners_3d)
ori3d.append(ori_3d)
raw_input()
bgcolor=(0,0,0)
fig = mlab.figure(figure=None, bgcolor=bgcolor, fgcolor=None, engine=None, size=(1600, 1000))
mlab.points3d(pc[:,0], pc[:,1], pc[:,2], pc[:,2], mode='point', colormap='gnuplot', figure=fig)
mlab.points3d(0, 0, 0, color=(1,1,1), mode='sphere', scale_factor=0.2)
draw_gt_boxes3d(box3d, fig=fig)
for i in range(len(ori3d)):
ori_3d = ori3d[i]
x1,y1,z1 = ori_3d[0,:]
x2,y2,z2 = ori_3d[1,:]
mlab.plot3d([x1, x2], [y1, y2], [z1,z2], color=(0.5,0.5,0.5), tube_radius=None, line_width=1, figure=fig)
mlab.orientation_axes()
for i,obj in enumerate(objects):
print('Orientation: ', i, np.arctan2(obj.orientation[1], obj.orientation[0]))
print('Dimension: ', i, obj.l, obj.w, obj.h)
raw_input()
if show_frustum:
img = sunrgbd.get_image(data_idx)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for i,obj in enumerate(objects):
box2d_fov_inds = (uv[:,0]<obj.xmax) & (uv[:,0]>=obj.xmin) & (uv[:,1]<obj.ymax) & (uv[:,1]>=obj.ymin)
box2d_fov_pc = pc[box2d_fov_inds, :]
img2 = np.copy(img)
cv2.rectangle(img2, (int(obj.xmin),int(obj.ymin)), (int(obj.xmax),int(obj.ymax)), (0,255,0), 2)
cv2.putText(img2, '%d %s'%(i,obj.classname), (max(int(obj.xmin),15), max(int(obj.ymin),15)), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255,0,0), 2)
Image.fromarray(img2).show()
fig = mlab.figure(figure=None, bgcolor=bgcolor, fgcolor=None, engine=None, size=(1000, 1000))
mlab.points3d(box2d_fov_pc[:,0], box2d_fov_pc[:,1], box2d_fov_pc[:,2], box2d_fov_pc[:,2], mode='point', colormap='gnuplot', figure=fig)
raw_input()