updated Python examples

dusty-nv · Jun 18, 2020 · 29f5896 · 29f5896
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diff --git a/python/examples/camera-viewer.py b/python/examples/camera-viewer.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/python3
 #
 # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
 #

diff --git a/python/examples/cuda-examples.py b/python/examples/cuda-examples.py
@@ -0,0 +1,99 @@
+#!/usr/bin/python3
+#
+# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+#
+
+import jetson.utils
+import argparse
+
+
+# parse the command line
+parser = argparse.ArgumentParser(description='Perform some example CUDA processing on an image')
+
+parser.add_argument("file_in", type=str, default="images/granny_smith_1.jpg", nargs='?', help="filename of the input image to process")
+parser.add_argument("file_out", type=str, default="cuda-example.jpg", nargs='?', help="filename of the output image to save")
+
+opt = parser.parse_args()
+
+
+# convert colorspace
+def convert_color(img, output_format):
+	converted_img = jetson.utils.cudaAllocMapped(width=img.width, height=img.height, format=output_format)
+	jetson.utils.cudaConvertColor(img, converted_img)
+	return converted_img
+
+
+# center crop an image
+def crop(img, crop_factor):
+	crop_border = ((1.0 - crop_factor[0]) * 0.5 * img.width,
+				(1.0 - crop_factor[1]) * 0.5 * img.height)
+
+	crop_roi = (crop_border[0], crop_border[1], img.width - crop_border[0], img.height - crop_border[1])
+
+	crop_img = jetson.utils.cudaAllocMapped(width=img.width * crop_factor[0],
+									height=img.height * crop_factor[1],
+									format=img.format)
+
+	jetson.utils.cudaCrop(img, crop_img, crop_roi)
+	return crop_img
+
+
+# resize an image
+def resize(img, resize_factor):
+	resized_img = jetson.utils.cudaAllocMapped(width=img.width * resize_factor[0],
+									   height=img.height * resize_factor[1],
+									   format=img.format)
+
+	jetson.utils.cudaResize(img, resized_img)
+	return resized_img
+
+
+# load the image
+input_img = jetson.utils.loadImage(opt.file_in)
+
+print('input image:')
+print(input_img)
+
+# convert to grayscale - other formats are:
+#  rgb8, rgba8, rgb32f, rgba32f, gray32f
+gray_img = convert_color(input_img, "gray8")
+
+print('grayscale image:')
+print(gray_img)
+
+# crop the image
+crop_img = crop(gray_img, (0.75, 0.75))
+
+print('cropped image:')
+print(crop_img)
+
+# resize the image
+resized_img = resize(crop_img, (0.5, 0.5))
+
+print('resized image:')
+print(resized_img)
+
+# save the image
+if opt.file_out is not None:
+	jetson.utils.cudaDeviceSynchronize()
+	jetson.utils.saveImage(opt.file_out, resized_img)
+	print("saved {:d}x{:d} test image to '{:s}'".format(crop_img.width, crop_img.height, opt.file_out))
+
diff --git a/python/examples/cuda-from-cv.py b/python/examples/cuda-from-cv.py
@@ -0,0 +1,65 @@
+#!/usr/bin/python3
+#
+# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+#
+
+import cv2
+import jetson.utils
+import argparse
+
+
+# parse the command line
+parser = argparse.ArgumentParser(description='Convert an image from OpenCV to CUDA')
+
+parser.add_argument("file_in", type=str, default="images/granny_smith_1.jpg", nargs='?', help="filename of the input image to process")
+parser.add_argument("file_out", type=str, default="cuda-from-cv.jpg", nargs='?', help="filename of the output image to save")
+
+opt = parser.parse_args()
+
+
+# load the image
+cv_img = cv2.imread(opt.file_in)
+
+print('OpenCV image size: ' + str(cv_img.shape))
+print('OpenCV image type: ' + str(cv_img.dtype))
+
+# convert to CUDA (cv2 images are numpy arrays, in BGR format)
+bgr_img = jetson.utils.cudaFromNumpy(cv_img, isBGR=True)
+
+print('BGR image: ')
+print(bgr_img)
+
+# convert from BGR -> RGB
+rgb_img = jetson.utils.cudaAllocMapped(width=bgr_img.width,
+							    height=bgr_img.height,
+							    format='rgb8')
+
+jetson.utils.cudaConvertColor(bgr_img, rgb_img)
+
+print('RGB image: ')
+print(rgb_img)
+
+# save the image
+if opt.file_out is not None:
+	jetson.utils.cudaDeviceSynchronize()
+	jetson.utils.saveImage(opt.file_out, rgb_img)
+	print("saved {:d}x{:d} test image to '{:s}'".format(rgb_img.width, rgb_img.height, opt.file_out))
+
diff --git a/python/examples/cuda-from-numpy.py b/python/examples/cuda-from-numpy.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/python3
 #
 # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
 #

diff --git a/python/examples/cuda-to-cv.py b/python/examples/cuda-to-cv.py
@@ -0,0 +1,67 @@
+#!/usr/bin/python3
+#
+# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the "Software"),
+# to deal in the Software without restriction, including without limitation
+# the rights to use, copy, modify, merge, publish, distribute, sublicense,
+# and/or sell copies of the Software, and to permit persons to whom the
+# Software is furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
+# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+# DEALINGS IN THE SOFTWARE.
+#
+
+import cv2
+import jetson.utils
+import argparse
+
+
+# parse the command line
+parser = argparse.ArgumentParser(description='Convert an image from CUDA to OpenCV')
+
+parser.add_argument("file_in", type=str, default="images/jellyfish.jpg", nargs='?', help="filename of the input image to process")
+parser.add_argument("file_out", type=str, default="cuda-to-cv.jpg", nargs='?', help="filename of the output image to save")
+
+opt = parser.parse_args()
+
+
+# load the image into CUDA memory
+rgb_img = jetson.utils.loadImage(opt.file_in)
+
+print('RGB image: ')
+print(rgb_img)
+
+# convert to BGR, since that's what OpenCV expects
+bgr_img = jetson.utils.cudaAllocMapped(width=rgb_img.width,
+							    height=rgb_img.height,
+							    format='bgr8')
+
+jetson.utils.cudaConvertColor(rgb_img, bgr_img)
+
+print('BGR image: ')
+print(bgr_img)
+
+# make sure the GPU is done work before we convert to cv2
+jetson.utils.cudaDeviceSynchronize()
+
+# convert to cv2 image (cv2 images are numpy arrays)
+cv_img = jetson.utils.cudaToNumpy(bgr_img)
+
+print('OpenCV image size: ' + str(cv_img.shape))
+print('OpenCV image type: ' + str(cv_img.dtype))
+
+# save the image
+if opt.file_out is not None:
+	cv2.imwrite(opt.file_out, cv_img)
+	print("saved {:d}x{:d} test image to '{:s}'".format(bgr_img.width, bgr_img.height, opt.file_out))
+
diff --git a/python/examples/cuda-to-numpy.py b/python/examples/cuda-to-numpy.py
@@ -1,6 +1,6 @@
-#!/usr/bin/python
+#!/usr/bin/python3
 #
-# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
+# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
 #
 # Permission is hereby granted, free of charge, to any person obtaining a
 # copy of this software and associated documentation files (the "Software"),
@@ -23,25 +23,23 @@
 
 import jetson.utils
 import argparse
-import ctypes
 import numpy
 
 # parse the command line
 parser = argparse.ArgumentParser('Map CUDA to memory to numpy ndarray')
 
 parser.add_argument("--width", type=int, default=4, help="width of the array (in float elements)")
 parser.add_argument("--height", type=int, default=2, help="height of the array (in float elements)")
-parser.add_argument("--depth", type=int, default=3, help="depth of the array (in float elements)")
 
 opt = parser.parse_args()
 
 # allocate cuda memory
-cuda_mem = jetson.utils.cudaAllocMapped(opt.height * opt.width * opt.depth * ctypes.sizeof(ctypes.c_float))
-print(cuda_mem)
+cuda_img = jetson.utils.cudaAllocMapped(width=opt.width, height=opt.height, format='rgb32f')
+print(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_mem, opt.width, opt.height, opt.depth)
+array = jetson.utils.cudaToNumpy(cuda_img)
 
 print("\ncudaToNumpy() array:")
 print(type(array))

diff --git a/python/examples/gl-display-test.py b/python/examples/gl-display-test.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/python3
 #
 # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
 #