Stavo cercando un metodo per aveere un set di training per Monocular Depth Estimation ed ho ritirato fuori la RealSense D415 per scoprire che ad Agosto 2021 la Intel ha dichiarato la dismissione di questi sensori robotici (ad esclusione di quelli stereoscopici).... mi ricorda tanto la storia di Intel Edison ed Intel Stick...progetti interessanti morti
Questo piccolo programmino (che modifica uno degli esempi dell'SDK di Realsense) salva la mappa di profondita' in formato NumPy ed la corrispondente immagine JPG premendo il tasto S
Per compilare in binario l'eseguibile
pyinstaller main.py --onefile
requirements.txt
altgraph==0.17.2
importlib-metadata==4.8.3
numpy==1.19.5
opencv-python==4.1.2.30
Pillow==8.4.0
pyinstaller==4.7
pyinstaller-hooks-contrib==2021.4
pyrealsense2==2.50.0.3812
typing_extensions==4.0.1
zipp==3.6.0
main.py
import sys,getopt
import pyrealsense2 as rs
import numpy as np
import cv2
from PIL import Image
import os.path
def completo(argv):
outputdir = ''
if len(sys.argv) < 2:
print('test.py -o <output_directory>')
sys.exit()
try:
opts, args = getopt.getopt(argv, "hi:o:", ["odir="])
except getopt.GetoptError:
print('test.py -o <output_directory>')
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print('test.py -o <output_directory>')
sys.exit()
elif opt in ("-o", "--odir"):
outputdir = arg
if (os.path.isdir(outputdir)) == False:
print('Errore nome directory output')
sys.exit()
print('Output file is ' + outputdir)
## License: Apache 2.0. See LICENSE file in root directory.
## Copyright(c) 2015-2017 Intel Corporation. All Rights Reserved.
###############################################
## Open CV and Numpy integration ##
###############################################
# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
# Get device product line for setting a supporting resolution
pipeline_wrapper = rs.pipeline_wrapper(pipeline)
pipeline_profile = config.resolve(pipeline_wrapper)
device = pipeline_profile.get_device()
device_product_line = str(device.get_info(rs.camera_info.product_line))
found_rgb = False
for s in device.sensors:
if s.get_info(rs.camera_info.name) == 'RGB Camera':
found_rgb = True
break
if not found_rgb:
print("The demo requires Depth camera with Color sensor")
exit(0)
contatore = 0
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
if device_product_line == 'L500':
config.enable_stream(rs.stream.color, 960, 540, rs.format.bgr8, 30)
else:
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)
# Start streaming
pipeline.start(config)
try:
while True:
# Wait for a coherent pair of frames: depth and color
frames = pipeline.wait_for_frames()
depth_frame = frames.get_depth_frame()
color_frame = frames.get_color_frame()
if not depth_frame or not color_frame:
continue
# Convert images to numpy arrays
depth_image = np.asanyarray(depth_frame.get_data())
color_image = np.asanyarray(color_frame.get_data())
# Apply colormap on depth image (image must be converted to 8-bit per pixel first)
depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
depth_colormap_dim = depth_colormap.shape
color_colormap_dim = color_image.shape
# If depth and color resolutions are different, resize color image to match depth image for display
if depth_colormap_dim != color_colormap_dim:
resized_color_image = cv2.resize(color_image, dsize=(depth_colormap_dim[1], depth_colormap_dim[0]),
interpolation=cv2.INTER_AREA)
images = np.hstack((resized_color_image, depth_colormap))
else:
images = np.hstack((color_image, depth_colormap))
# Show images
cv2.namedWindow('Immagine', cv2.WINDOW_AUTOSIZE)
cv2.imshow('Immagine' , images)
tasto = cv2.waitKey(1000)
#print(str(tasto))
if (tasto == 115): #S
#salva su file
contatore = contatore + 1
str_conta = str(contatore)
try:
np.save(str_conta.zfill(3)+'_depth.npy', depth_image)
im = Image.fromarray(color_image)
im.save(str_conta.zfill(3)+"_color.jpg")
print('Immagine ' + str(contatore) + 'acquisita')
except:
print('Errore acquisizione')
exit()
if (tasto == 113): #Q
exit()
finally:
# Stop streaming
pipeline.stop()
if __name__ == '__main__':
completo(sys.argv[1:])
