cton.py

#!/usr/bin/python3
#
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#

import cv2
import jetson.utils
import argparse
import numpy

# allocate cuda memory
imput = jetson.utils.videoSource("file:///jetson-inference/data/images/", )
cuda_img = imput.Capture()

cv2_img = cv2.imread('/jetson-inference/data/images/airplane_0.jpg') #The function to read from an image into OpenCv is imread()


print('*** cuda_img ***\n', cuda_img)

# create a numpy ndarray that references the CUDA memory
# it won't be copied, but uses the same memory underneath
array = jetson.utils.cudaToNumpy(cuda_img)

print("*** cv2_img ***")
print(type(cv2_img))
print(cv2_img.dtype)
print(cv2_img.shape)      # numpy dims will be in (height, width, depth) order
print(cv2_img)

print("cudaToNumpy() array:")
print(type(array))
print(array.dtype)
print(array.shape)	# numpy dims will be in (height, width, depth) order
print(array)

# sudo apt-get install ros-$(rosversion -d)-cv-bridge
# tal vez haya que hacer un "bgr --> rgb" antes!
ros_img = bridge.cv2_to_imgmsg(array, encoding="passthrough")

# create another ndarray and do some ops with it
#array2 = numpy.ones(array.shape, numpy.float32)

#print("\nadding arrays...\n")
#print(array + array2)