def visualize_dataset(dataset_dir):
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # NOQA
from chainercv.utils import read_image
from visualizations import vis_point, vis_edge
dataset = HandDBBaseDataset(dataset_dir, debug=True, mode="train")
example = dataset.get_example(0)
rgb_joint = example["rgb_joint"]
rgb_path = example["rgb_path"]
img = read_image(rgb_path)
fig = plt.figure(figsize=(5, 10))
ax1 = fig.add_subplot(211)
ax3 = fig.add_subplot(212, projection="3d")
rgb_vu = RGB_CAMERA_INTR.zyx2vu(rgb_joint)
color = [COLOR_MAP[k] for k in STANDARD_KEYPOINT_NAMES]
edge_color = [COLOR_MAP[s, t] for s, t in EDGES]
vis_point(rgb_vu, img=img, color=color, ax=ax1)
vis_edge(rgb_vu, indices=EDGES, color=edge_color, ax=ax1)
vis_point(rgb_joint, color=color, ax=ax3)
vis_edge(rgb_joint, indices=EDGES, color=edge_color, ax=ax3)
for ax in [ax3]:
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
ax.view_init(-65, -90)
plt.show()
def visualize_dataset(dataset_dir):
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # NOQA
from chainercv.utils import read_image
from visualizations import vis_point, vis_edge
dataset = GANeratedBaseDataset(dataset_dir, debug=False, mode="train")
idx = np.random.choice(len(dataset))
print(idx, len(dataset))
example = dataset.get_example(idx)
rgb_joint = example["rgb_joint"]
rgb_path = example["rgb_path"]
rgb = read_image(rgb_path)
fig = plt.figure(figsize=(5, 10))
ax2 = fig.add_subplot(211)
ax4 = fig.add_subplot(212, projection="3d")
color = [COLOR_MAP[k] for k in KEYPOINT_NAMES]
edge_color = [COLOR_MAP[s, t] for s, t in EDGES]
rgb_vu = example["rgb_camera"].zyx2vu(rgb_joint)
vis_point(rgb_vu, img=rgb, color=color, ax=ax2)
vis_edge(rgb_vu, indices=EDGES, color=edge_color, ax=ax2)
vis_point(rgb_joint, color=color, ax=ax4)
vis_edge(rgb_joint, indices=EDGES, color=edge_color, ax=ax4)
for ax in [ax4]:
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
ax.view_init(-65, -90)
plt.show()
def visualize_dataset(dataset_dir):
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # NOQA
from chainercv.utils import read_image
from visualizations import vis_point, vis_edge
dataset = MultiViewBaseDataset(dataset_dir, debug=False)
print(len(dataset))
i = np.random.choice(len(dataset))
example = dataset.get_example(i)
rgb_path = example["rgb_path"]
rgb_joint = example["rgb_joint"]
print(rgb_path)
img = read_image(rgb_path)
fig = plt.figure(figsize=(8, 8))
ax1 = fig.add_subplot(211)
ax3 = fig.add_subplot(212, projection="3d")
rgb_vu = dataset.rgb_camera.zyx2vu(rgb_joint)
color = [COLOR_MAP[k] for k in STANDARD_KEYPOINT_NAMES]
edge_color = [COLOR_MAP[s, t] for s, t in EDGES]
vis_point(rgb_vu, img=img, color=color, ax=ax1)
vis_edge(rgb_vu, indices=EDGES, color=edge_color, ax=ax1)
vis_point(rgb_joint, color=color, ax=ax3)
vis_edge(rgb_joint, indices=EDGES, color=edge_color, ax=ax3)
for ax in [ax3]:
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
ax.view_init(-65, -90)
plt.show()
def visualize_dataset(dataset_dir):
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # NOQA
from chainercv.utils import read_image
from visualizations import vis_point, vis_edge
dataset = FHADBaseDataset(dataset_dir, debug=True, mode="train")
example = dataset.get_example(0)
camera_joint = example["rgb_joint"]
depth_joint = example["depth_joint"]
rgb_path = example["rgb_path"]
depth_path = example["depth_path"]
img = read_image(rgb_path)
depth = dataset.read_depth(depth_path)
fig = plt.figure(figsize=(8, 8))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
ax3 = fig.add_subplot(223, projection="3d")
ax4 = fig.add_subplot(224, projection="3d")
rgb_vu = RGB_CAMERA_INTR.zyx2vu(camera_joint)
color = [COLOR_MAP[k] for k in KEYPOINT_NAMES]
edge_color = [COLOR_MAP[s, t] for s, t in EDGES]
depth_vu = DEPTH_CAMERA_INTR.zyx2vu(depth_joint)
vis_point(rgb_vu, img=img, color=color, ax=ax1)
vis_edge(rgb_vu, indices=EDGES, color=edge_color, ax=ax1)
vis_point(depth_vu, img=depth, color=color, ax=ax2)
vis_edge(depth_vu, indices=EDGES, color=edge_color, ax=ax2)
vis_point(camera_joint, color=color, ax=ax3)
vis_edge(camera_joint, indices=EDGES, color=edge_color, ax=ax3)
vis_point(depth_joint, color=color, ax=ax4)
vis_edge(depth_joint, indices=EDGES, color=edge_color, ax=ax4)
for ax in [ax3, ax4]:
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_zlabel("z")
ax.view_init(-65, -90)
plt.show()