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from __future__ import print_function
import argparse
import glob
from pathlib import Path
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import proj3d
from PIL import Image
print(f"matplotlib version: {matplotlib.__version__}")
abort = False
def close_figure(event):
plt.close(event.canvas.figure)
if event.key == 'escape':
global abort
abort = True
def load_data(iter, input_color_filenames, input_infrared_filenames, input_depth_filenames, input_pcl_filenames):
color_filename = input_color_filenames[iter]
ir_filename = input_infrared_filenames[iter]
depth_filename = input_depth_filenames[iter]
pcl_filename = input_pcl_filenames[iter]
if not Path(color_filename).is_file():
color = np.zeros((480,640,3), dtype=np.uint8)
else:
color = Image.open(color_filename)
if not Path(ir_filename).is_file():
infrared = np.zeros((480,640,1), dtype=np.uint8)
else:
infrared = Image.open(ir_filename)
if not Path(depth_filename).is_file():
depth = np.zeros((480,640,1), dtype=np.uint8)
else:
with np.load(depth_filename) as data:
height = data['height'][0]
width = data['width'][0]
depth_data_raw = data['data'].reshape((height, width))
max_uint16 = 65536
hist, bin_edges = np.histogram(depth_data_raw, bins=max_uint16, range=(0, max_uint16-1))
# https://stackoverflow.com/a/30460089
dx = bin_edges[1] - bin_edges[0]
cumsum = np.cumsum(hist)*dx
depth = np.zeros(depth_data_raw.shape, dtype=np.uint8)
for i in range(depth_data_raw.shape[0]):
for j in range(depth_data_raw.shape[1]):
try:
depth_value = depth_data_raw[i,j]
if depth_value > 0:
depth[i,j] = np.uint8(cumsum[depth_value] * 255.0 / cumsum[-1])
except:
raise
if not Path(pcl_filename).is_file():
pointcloud = np.zeros((480,640,3), dtype=np.float)
else:
with np.load(pcl_filename) as data:
height = data['height'][0]
width = data['width'][0]
channel = data['channel'][0]
pointcloud = data['data']
assert(len(pointcloud.shape) == 3)
assert(pointcloud.shape[0] == height)
assert(pointcloud.shape[1] == width)
assert(pointcloud.shape[2] == channel)
return color, infrared, depth, pointcloud
def main():
parser = argparse.ArgumentParser(description='Plot color/IR/depth (in npz fileformat) data stored with visp-save-rs-dataset.cpp file.',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-i', '--input', type=str, default="",
help='Input data folder.')
parser.add_argument('--color-pattern', type=str, default="color_image_*.png",
help='Filename pattern for the color images.')
parser.add_argument('--infrared-pattern', type=str, default="infrared_image_*.png",
help='Filename pattern for the infrared images.')
parser.add_argument('--depth-pattern', type=str, default="depth_image_*.npz",
help='Filename pattern for the depth images.')
parser.add_argument('--pcl-pattern', type=str, default="point_cloud_*.npz",
help='Filename pattern for the pointcloud data.')
parser.add_argument('--pcl-subsample', type=int, default=10,
help='Pointcloud subsampling.')
args = parser.parse_args()
input_folder = Path(args.input)
color_pattern = Path(input_folder) / args.color_pattern
infrared_pattern = Path(input_folder) / args.infrared_pattern
depth_pattern = Path(input_folder) / args.depth_pattern
pcl_pattern = Path(input_folder) / args.pcl_pattern
pcl_subsample = args.pcl_subsample
print(f"Input folder: {input_folder}")
print(f"Color filename pattern: {color_pattern}")
print(f"Infrared filename pattern: {infrared_pattern}")
print(f"Depth filename pattern: {depth_pattern}")
print(f"Pointcloud filename pattern: {pcl_pattern}")
print(f"Pointcloud subsampling: {pcl_subsample}")
if not input_folder.is_dir():
print(f"Invalid folder: {input_folder}")
return
input_color_filenames = sorted(glob.glob(str(color_pattern)))
input_infrared_filenames = sorted(glob.glob(str(infrared_pattern)))
input_depth_filenames = sorted(glob.glob(str(depth_pattern)))
input_pcl_filenames = sorted(glob.glob(str(pcl_pattern)))
max_data = max(len(input_color_filenames), len(input_infrared_filenames), len(input_depth_filenames), len(input_pcl_filenames))
if max_data == 0:
raise ValueError('Input data are empty.')
max_value = 1e9
nb_color = max_value if len(input_color_filenames) == 0 else len(input_color_filenames)
nb_infrared = max_value if len(input_infrared_filenames) == 0 else len(input_infrared_filenames)
nb_depth = max_value if len(input_depth_filenames) == 0 else len(input_depth_filenames)
nb_pcl = max_value if len(input_pcl_filenames) == 0 else len(input_pcl_filenames)
max_data = min(nb_color, nb_infrared, nb_depth, nb_pcl)
# Truncate data if needed
print(f"Nb color: {len(input_color_filenames)} ; IR: {len(input_infrared_filenames)} ;\
depth: {len(input_depth_filenames)} ; PCL: {len(input_pcl_filenames)} ; Truncate data to: {max_data}")
input_color_filenames = [""] * max_data if len(input_color_filenames) == 0 else input_color_filenames[:max_data]
input_infrared_filenames = [""] * max_data if len(input_infrared_filenames) == 0 else input_infrared_filenames[:max_data]
input_depth_filenames = [""] * max_data if len(input_depth_filenames) == 0 else input_depth_filenames[:max_data]
input_pcl_filenames = [""] * max_data if len(input_pcl_filenames) == 0 else input_pcl_filenames[:max_data]
color_vec = []
ir_vec = []
depth_vec = []
pcl_vec = []
color_data, ir_data, depth_data, pcl_data = load_data(0, input_color_filenames, input_infrared_filenames, input_depth_filenames, input_pcl_filenames)
color_vec.append(color_data)
ir_vec.append(ir_data)
depth_vec.append(depth_data)
pcl_vec.append(pcl_data)
# https://matplotlib.org/stable/gallery/mplot3d/mixed_subplots.html
# https://matplotlib.org/stable/gallery/mplot3d/subplot3d.html
fig = plt.figure()
title = fig.suptitle('RGB + IR + Depth + PCL ({}/{})'.format(1, max_data), fontsize=30)
ax00 = fig.add_subplot(2, 2, 1)
ax01 = fig.add_subplot(2, 2, 2)
ax10 = fig.add_subplot(2, 2, 3)
ax11 = fig.add_subplot(2, 2, 4, projection='3d')
im0 = ax00.imshow(color_vec[0])
im1 = ax01.imshow(ir_vec[0], cmap='gray')
im2 = ax10.imshow(depth_vec[0])
im3 = ax11.scatter(pcl_vec[0][::pcl_subsample,::pcl_subsample,0],
pcl_vec[0][::pcl_subsample,::pcl_subsample,1],
pcl_vec[0][::pcl_subsample,::pcl_subsample,2])
def init():
im0.set_array(color_vec[0])
im1.set_array(ir_vec[0])
im2.set_array(depth_vec[0])
subsample = pcl_vec[0][::pcl_subsample,::pcl_subsample,:2]
# https://stackoverflow.com/a/9416663
im3.set_offsets(subsample.reshape(-1,2))
im3.set_array(pcl_vec[0][::pcl_subsample,::pcl_subsample,2].flatten())
# https://stackoverflow.com/a/57259405
def update_func(frame):
if frame >= len(color_vec):
color_data, ir_data, depth_data, pcl_data = load_data(frame, input_color_filenames,
input_infrared_filenames, input_depth_filenames,
input_pcl_filenames)
color_vec.append(color_data)
ir_vec.append(ir_data)
depth_vec.append(depth_data)
pcl_vec.append(pcl_data)
im0.set_array(color_vec[frame])
im1.set_array(ir_vec[frame])
im2.set_array(depth_vec[frame])
# Did not found a way to simultaneously update scatter data and the axis limits
# So here we clear and replot the data
subsample_xy = pcl_vec[frame][::pcl_subsample,::pcl_subsample,:2].reshape(-1,2)
subsample_z = pcl_vec[frame][::pcl_subsample,::pcl_subsample,2].flatten()
ax11.clear()
im3 = ax11.scatter(subsample_xy[:,0],
subsample_xy[:,1],
subsample_z)
ax11.set_xlabel('X')
ax11.set_ylabel('Y')
ax11.set_zlabel('Z')
# # This does not work
# ax11.clear()
# # https://stackoverflow.com/a/27741495
# corners = (min(subsample_xy[:,0]), min(subsample_xy[:,1]), min(subsample_z)), \
# (max(subsample_xy[:,0]), max(subsample_xy[:,1]), max(subsample_z))
# print(f"corners={corners}")
# ax11.update_datalim(corners)
# ax11.margins(0.05, 0.05, 0.05)
# ax11.autoscale_view()
# im3.set_offsets(subsample_xy)
# im3.set_array(subsample_z)
# ax11.add_collection(im3)
title.set_text('RGB + IR + Depth + PCL ({}/{})'.format(frame+1, max_data))
# https://matplotlib.org/stable/api/animation_api.html
anim = animation.FuncAnimation(
fig,
update_func,
frames = np.arange(len(input_color_filenames)),
interval = 33, # in ms
init_func = init
)
plt.gcf().canvas.mpl_connect('key_press_event', close_figure)
plt.show(block=False)
plt.pause(0.033)
if abort:
return
if __name__ == '__main__':
main()
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