qingswu

## tf_data_augmentation_on_gpu.py
def augment(images, labels,
            resize=None, # (width, height) tuple or None
            horizontal_flip=False,
            vertical_flip=False,
            rotate=0, # Maximum rotation angle in degrees
            crop_probability=0, # How often we do crops
            crop_min_percent=0.6, # Minimum linear dimension of a crop
            crop_max_percent=1.,  # Maximum linear dimension of a crop
            mixup=0):  # Mixup coeffecient, see https://arxiv.org/abs/1710.09412.pdf
  if resize is not None:

## print_common_module_versions.py
def get_versions():
  versions = []

  import sys
  versions.append('Python verison: {}.{}.{}'.format(sys.version_info.major, sys.version_info.minor, sys.version_info.micro))

  import cv2
  versions.append('OpenCV: {}'.format(cv2.__version__))

  import numpy as np

## vidoe_cap_proc.cpp
#include <opencv2/highgui.hpp>
#include <opencv2/videoio.hpp>

int main(int argc, char** argv) {
  cv::VideoCapture cap(0);
  // cap.set(cv::CAP_PROP_FRAME_WIDTH, 1280);
  // cap.set(cv::CAP_PROP_FRAME_HEIGHT, 720);

  cv::Mat im;

## client.cpp
/**
 * OpenCV video streaming over TCP/IP
 * Client: Receives video from server and display it
 * by Steve Tuenkam
 */

#include "opencv2/opencv.hpp"
#include <sys/socket.h>
#include <arpa/inet.h>
#include <unistd.h>

## eggs_detector.cpp
/**
 * @brief     Image enchancement and Hough transform example
 * @author    Eugene Khvedchenya <ekhvedchenya@gmail.com>
 * @copyright computer-vision-talks.com/articles/how-to-detect-circles-in-noisy-image/
 */


#include <opencv2/opencv.hpp>

## cmake_deploy.sh
# create new build dir
rm -rf build
cd build
cmake .. # some options
cmake --build . --config release --target install # build install
cmake --build . --config releasee --target clean # cleanup

## gist:1c688af97953c2833c96c43092e94c72
cmake -DWITH_CUDA=ON -DWITH_CUFFT=ON -DWITH_CUBLAS=ON -DCMAKE_BUILD_TYPE=Release -DOPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules -DBUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_DOCS=OFF -DCUDA_ARCH_BIN=3.0 -DCUDA_ARCH_PTX=3.0 -DPYTHON2_LIBRARY=$(python-config --prefix)/lib/libpython2.7.dylib -DPYTHON2_INCLUDE_DIR=$(python-config --prefix)/include/python2.7 ..

## minmax_rc.py
#!/usr/bin/env python
from glob import glob
import cv2

jpgs = glob('./*.jpg')
shapes = [cv2.imread(f).shape for f in jpgs]
a = [list(i) for i in shapes]
width = [row[1] for row in a]
height = [row[0] for row in a]
print 'width min:', min(width), ', max:', max(width), '; height min:', min(height), ', max:', max(height)

## png2jpg.py
#!/usr/bin/env python
from glob import glob
import cv2
pngs = glob('./*.png')

for j in pngs:
    img = cv2.imread(j)
    cv2.imwrite(j[:-3] + 'jpg', img)

## for_each_macro
// Accept any number of args >= N, but expand to just the Nth one.
// Here, N == 6.
#define _GET_NTH_ARG(_1, _2, _3, _4, _5, N, ...) N

// Define some macros to help us create overrides based on the
// arity of a for-each-style macro.
#define _fe_0(_call, ...)
#define _fe_1(_call, x) _call(x)
#define _fe_2(_call, x, ...) _call(x) _fe_1(_call, __VA_ARGS__)
#define _fe_3(_call, x, ...) _call(x) _fe_2(_call, __VA_ARGS__)
	def augment(images, labels,
	resize=None, # (width, height) tuple or None
	horizontal_flip=False,
	vertical_flip=False,
	rotate=0, # Maximum rotation angle in degrees
	crop_probability=0, # How often we do crops
	crop_min_percent=0.6, # Minimum linear dimension of a crop
	crop_max_percent=1., # Maximum linear dimension of a crop
	mixup=0): # Mixup coeffecient, see https://arxiv.org/abs/1710.09412.pdf
	if resize is not None:
	def get_versions():
	versions = []

	import sys
	versions.append('Python verison: {}.{}.{}'.format(sys.version_info.major, sys.version_info.minor, sys.version_info.micro))

	import cv2
	versions.append('OpenCV: {}'.format(cv2.__version__))

	import numpy as np
	#include <opencv2/highgui.hpp>
	#include <opencv2/videoio.hpp>

	int main(int argc, char** argv) {
	cv::VideoCapture cap(0);
	// cap.set(cv::CAP_PROP_FRAME_WIDTH, 1280);
	// cap.set(cv::CAP_PROP_FRAME_HEIGHT, 720);

	cv::Mat im;
	/**
	* OpenCV video streaming over TCP/IP
	* Client: Receives video from server and display it
	* by Steve Tuenkam
	*/

	#include "opencv2/opencv.hpp"
	#include <sys/socket.h>
	#include <arpa/inet.h>
	#include <unistd.h>
	/**
	* @brief Image enchancement and Hough transform example
	* @author Eugene Khvedchenya <ekhvedchenya@gmail.com>
	* @copyright computer-vision-talks.com/articles/how-to-detect-circles-in-noisy-image/
	*/



	#include <opencv2/opencv.hpp>
	# create new build dir
	rm -rf build
	cd build
	cmake .. # some options
	cmake --build . --config release --target install # build install
	cmake --build . --config releasee --target clean # cleanup
	#!/usr/bin/env python
	from glob import glob
	import cv2

	jpgs = glob('./*.jpg')
	shapes = [cv2.imread(f).shape for f in jpgs]
	a = [list(i) for i in shapes]
	width = [row[1] for row in a]
	height = [row[0] for row in a]
	print 'width min:', min(width), ', max:', max(width), '; height min:', min(height), ', max:', max(height)
	// Accept any number of args >= N, but expand to just the Nth one.
	// Here, N == 6.
	#define _GET_NTH_ARG(_1, _2, _3, _4, _5, N, ...) N

	// Define some macros to help us create overrides based on the
	// arity of a for-each-style macro.
	#define _fe_0(_call, ...)
	#define _fe_1(_call, x) _call(x)
	#define _fe_2(_call, x, ...) _call(x) _fe_1(_call, __VA_ARGS__)
	#define _fe_3(_call, x, ...) _call(x) _fe_2(_call, __VA_ARGS__)