def image_cb(self, msg):
img = self.bridge.imgmsg_to_cv2(msg, desired_encoding='rgb8')
resized_img = cv2.resize(img, (self.resized_W, self.resized_H))
H, W, _ = img.shape
y_scale = self.resized_H / H
x_scale = self.resized_W / W
poses, _ = self.engine.DetectPosesInImage(resized_img.astype(np.uint8))
poses_msg = PeoplePoseArray()
poses_msg.header = msg.header
points = []
visibles = []
for pose in poses:
if pose.score < self.score_thresh:
continue
pose_msg = PeoplePose()
point = []
visible = []
for lbl, keypoint in pose.keypoints.items():
resized_key_y, resized_key_x = keypoint.yx
key_y = resized_key_y / y_scale
key_x = resized_key_x / x_scale
point.append((key_y, key_x))
if keypoint.score < self.joint_score_thresh:
visible.append(False)
continue
pose_msg.limb_names.append(lbl)
pose_msg.scores.append(keypoint.score)
pose_msg.poses.append(Pose(position=Point(x=key_x, y=key_y)))
visible.append(True)
poses_msg.poses.append(pose_msg)
points.append(point)
visibles.append(visible)
self.pub_pose.publish(poses_msg)
points = np.array(points, dtype=np.int32)
visibles = np.array(visibles, dtype=np.bool)
if self.visualize:
fig = plt.figure(tight_layout={'pad': 0})
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.axis('off')
fig.add_axes(ax)
vis_point(img.transpose((2, 0, 1)), points, visibles, ax=ax)
fig.canvas.draw()
w, h = fig.canvas.get_width_height()
vis_img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8)
vis_img.shape = (h, w, 3)
fig.clf()
plt.close()
vis_msg = self.bridge.cv2_to_imgmsg(vis_img, 'rgb8')
# BUG: https://answers.ros.org/question/316362/sensor_msgsimage-generates-float-instead-of-int-with-python3/ # NOQA
vis_msg.step = int(vis_msg.step)
vis_msg.header = msg.header
self.pub_image.publish(vis_msg)
def image_cb(self, msg):
img = self.bridge.imgmsg_to_cv2(msg, desired_encoding='rgb8')
resized_img = cv2.resize(img, (641, 481))
poses, _ = self.engine.DetectPosesInImage(resized_img.astype(np.uint8))
poses_msg = PeoplePoseArray()
poses_msg.header = msg.header
points = []
visibles = []
for pose in poses:
if pose.score < self.score_thresh:
continue
pose_msg = PeoplePose()
point = []
visible = []
for lbl, keypoint in pose.keypoints.items():
point.append(keypoint.yx)
if keypoint.score < self.joint_score_thresh:
visible.append(False)
continue
pose_msg.limb_names.append(lbl)
pose_msg.scores.append(keypoint.score)
pose_msg.poses.append(
Pose(position=Point(x=keypoint.yx[1],
y=keypoint.yx[0])))
visible.append(True)
poses_msg.poses.append(pose_msg)
points.append(point)
visibles.append(visible)
self.pub_pose.publish(poses_msg)
points = np.array(points, dtype=np.int32)
visibles = np.array(visibles, dtype=np.bool)
if self.visualize:
vis_img = resized_img.transpose(2, 0, 1)
vis_point(vis_img, points, visibles)
fig = plt.gcf()
fig.canvas.draw()
w, h = fig.canvas.get_width_height()
vis_img = np.fromstring(
fig.canvas.tostring_rgb(), dtype=np.uint8)
fig.clf()
vis_img.shape = (h, w, 3)
plt.close()
vis_msg = self.bridge.cv2_to_imgmsg(vis_img, 'rgb8')
# BUG: https://answers.ros.org/question/316362/sensor_msgsimage-generates-float-instead-of-int-with-python3/ # NOQA
vis_msg.step = int(vis_msg.step)
vis_msg.header = msg.header
self.pub_image.publish(vis_msg)
def test_vis_point(self):
img = np.random.randint(
0, 255, size=(3, 32, 32)).astype(np.float32)
point = np.random.uniform(size=(3, 2)).astype(np.float32)
ax = vis_point(img, point, self.mask)
self.assertTrue(isinstance(ax, matplotlib.axes.Axes))
def test_vis_point(self):
if optional_modules:
img = np.random.randint(
0, 255, size=(3, 32, 32)).astype(np.float32)
point = np.random.uniform(size=(3, 2)).astype(np.float32)
ax = vis_point(img, point, self.mask)
self.assertTrue(isinstance(ax, matplotlib.axes.Axes))
def visualize_cb(self, event):
if (not self.visualize or self.img is None or self.points is None
or self.visibles is None):
return
with self.lock:
img = self.img.copy()
header = copy.deepcopy(self.header)
points = self.points.copy()
visibles = self.visibles.copy()
fig = plt.figure(tight_layout={'pad': 0})
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.axis('off')
fig.add_axes(ax)
vis_point(img.transpose((2, 0, 1)), points, visibles, ax=ax)
fig.canvas.draw()
w, h = fig.canvas.get_width_height()
vis_img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8)
vis_img.shape = (h, w, 3)
fig.clf()
plt.close()
if self.pub_image.get_num_connections() > 0:
vis_msg = self.bridge.cv2_to_imgmsg(vis_img, 'rgb8')
# BUG: https://answers.ros.org/question/316362/sensor_msgsimage-generates-float-instead-of-int-with-python3/ # NOQA
vis_msg.step = int(vis_msg.step)
vis_msg.header = header
self.pub_image.publish(vis_msg)
if self.pub_image_compressed.get_num_connections() > 0:
# publish compressed http://wiki.ros.org/rospy_tutorials/Tutorials/WritingImagePublisherSubscriber # NOQA
vis_compressed_msg = CompressedImage()
vis_compressed_msg.header = header
vis_compressed_msg.format = "jpeg"
vis_img_rgb = cv2.cvtColor(vis_img, cv2.COLOR_BGR2RGB)
vis_compressed_msg.data = np.array(
cv2.imencode('.jpg', vis_img_rgb)[1]).tostring()
self.pub_image_compressed.publish(vis_compressed_msg)
video_id, frame_id = self._get_ids(i)
anno = self.annos[self.video_names[video_id]]
poly = np.array(anno['gt_rect'][frame_id])
if len(poly) == 8:
poly = poly.reshape((4, 2))[:, ::-1] # y,x
elif len(poly) == 4:
x = poly[0]
y = poly[1]
w = poly[2]
h = poly[3]
poly = np.array((
(y, x),
(y, x + w),
(y + h, x + w),
(y + h, x)), dtype=np.float32)
return poly[None]
if __name__ == '__main__':
from chainercv.visualizations import vis_bbox
from chainercv.visualizations import vis_point
import matplotlib.pyplot as plt
dataset = VOTTrackingDataset('../../data')
print(dataset.video_names[14])
img, bbox, poly = dataset.slice[:, ['img', 'bbox', 'poly']][4322]
vis_bbox(img, bbox)
plt.savefig('b.png')
vis_point(img, poly)
plt.savefig('a.png')