TEMPLATE_HEADER
void STORAGE::resize(){
size_t newsize = resizer(table_size);
DataStorer ** newtable = new DataStorer*[newsize];
typename DataStorer::iterator it;
for (int i = 0; i < table_size; i++) {
if( table[i] != 0 ){
for (it = table[i]->begin(); it != table[i]->end(); it++) {
push( it->second.k, it->second.d, newtable, newsize);
}
delete table[i]; table[i] = 0;
}
}
delete [] table;
table = newtable;
table_size = newsize;
updatePerfMeasure();
}
int main(int argc, const char** argv) {
RectResizer resizer(*ORIG_SIZE, *NEW_SIZE);
Segment scan(resizer.resize(cv::Rect(63, 112, 107, 48)), "SCAN", " ");
Segment hold(resizer.resize(cv::Rect(170, 108, 111, 51)), "HOLD", " ");
scan.setThreshold(0.01);
hold.setThreshold(0.01);
Digit* d[NUM_OF_DIGITS];
d[0] = new Digit(resizer.resize(cv::Rect(45, 182, 112, 214)));
d[1] = new Digit(resizer.resize(cv::Rect(156, 182, 112, 214)));
d[2] = new Digit(resizer.resize(cv::Rect(272, 182, 103, 214)));
d[3] = new Digit(resizer.resize(cv::Rect(419, 179, 105, 214)));
cv::Mat image;
/*
//From pictures
for (int im = 1; im < argc; im++) {
image = readImage(argc, argv, im);
readData(image, d, scan, hold);
printData(d, scan, hold);
showImage(image, d, scan, hold);
cv::waitKey(0);
}
*/
cv::VideoCapture cap;
openCamera(cap, argc, argv);
bool paused = false;
cv::Mat frame;
for (;;) {
if (!paused) {
cap >> frame;
if (frame.empty()) {
break;
}
}
frame.copyTo(image);
readData(image, d, scan, hold);
printData(d, scan, hold);
showImage(image, d, scan, hold);
char c = (char) cv::waitKey(10);
if (c == 27)
break;
switch (c) {
case 'p':
paused = !paused;
break;
default:
;
}
}
//-----------------------------------------------------------------------------
bool test_image_io(const std::string filename,
const main_params& mp,
const cropper_params& rp,
const resizer_params& sp,
const augmenter_params& ap)
{
int transform_idx = 0;
int mean_extractor_idx = -1;
unsigned int num_bytes = mp.m_num_bytes; // size of image in bytes
lbann::cv_process pp;
{ // Initialize the image processor
if (rp.m_is_set) { // If cropper parameters are given
// Setup a cropper
std::unique_ptr<lbann::cv_cropper> cropper(new(lbann::cv_cropper));
cropper->set(rp.m_crop_sz.first, rp.m_crop_sz.second, rp.m_rand_center, rp.m_roi_sz, rp.m_adaptive_interpolation);
pp.add_transform(std::move(cropper));
num_bytes = rp.m_crop_sz.first * rp.m_crop_sz.second * 3;
transform_idx ++;
}
if (sp.m_is_set) { // If resizer parameters are given
// Setup a cropper
std::unique_ptr<lbann::cv_resizer> resizer(new(lbann::cv_resizer));
resizer->set(sp.m_width, sp.m_height, rp.m_adaptive_interpolation);
pp.add_transform(std::move(resizer));
num_bytes = sp.m_width * sp.m_height * 3;
transform_idx ++;
}
if (ap.m_is_set) { // Set up an augmenter
std::unique_ptr<lbann::cv_augmenter> augmenter(new(lbann::cv_augmenter));
augmenter->set(ap.m_hflip, ap.m_vflip, ap.m_rot, ap.m_hshift, ap.m_vshift, ap.m_shear);
pp.add_transform(std::move(augmenter));
transform_idx ++;
}
if (mp.m_enable_colorizer) { // Set up a colorizer
std::unique_ptr<lbann::cv_colorizer> colorizer(new(lbann::cv_colorizer));
pp.add_transform(std::move(colorizer));
transform_idx ++;
}
if (mp.m_enable_decolorizer) { // Set up a colorizer
std::unique_ptr<lbann::cv_decolorizer> decolorizer(new(lbann::cv_decolorizer));
pp.add_transform(std::move(decolorizer));
transform_idx ++;
}
if (mp.m_enable_mean_extractor) { // set up a mean extractor
mean_extractor_idx = transform_idx;
std::unique_ptr<lbann::cv_mean_extractor> mean_extractor(new(lbann::cv_mean_extractor));
if (rp.m_is_set)
mean_extractor->set(rp.m_crop_sz.first, rp.m_crop_sz.second, 3, mp.m_mean_batch_size);
else
mean_extractor->set(mp.m_mean_batch_size);
pp.add_transform(std::move(mean_extractor));
transform_idx ++;
}
if (!mp.is_normalizer_off()) { // Set up a normalizer
if (mp.is_channel_wise_normalizer()) {
std::unique_ptr<lbann::cv_normalizer> normalizer(new(lbann::cv_normalizer));
normalizer->z_score(true);
pp.add_normalizer(std::move(normalizer));
} else {
std::unique_ptr<lbann::cv_subtractor> normalizer(new(lbann::cv_subtractor));
#if 0
cv::Mat img_to_sub = cv::imread(mp.m_mean_image_name);
if (img_to_sub.empty()) {
std::cout << mp.m_mean_image_name << " does not exist" << std::endl;
return false;
}
normalizer->set_mean(img_to_sub);
#else
std::vector<lbann::DataType> mean = {0.40625, 0.45703, 0.48047};
normalizer->set_mean(mean);
std::vector<lbann::DataType> stddev = {0.3, 0.5, 0.3};
normalizer->set_stddev(stddev);
#endif
pp.add_normalizer(std::move(normalizer));
}
transform_idx ++;
}
}
// Load an image bytestream into memory
std::vector<unsigned char> buf;
bool ok = lbann::load_file(filename, buf);
if (!ok) {
std::cout << "Failed to load" << std::endl;
return false;
}
int width = 0;
int height = 0;
int type = 0;
::Mat Images;
::Mat Image_v; // matrix view
Images.Resize(((num_bytes==0)? 1: num_bytes), 2); // minibatch
size_t img_begin = 0;
size_t img_end = buf.size();
for (unsigned int i=0; i < mp.m_num_iter; ++i)
{
// This has nothing to do with the image type but only to create view on a block of bytes
using InputBuf_T = lbann::cv_image_type<uint8_t>;
// Construct a zero copying view to a portion of a preloaded data buffer
const cv::Mat inbuf(1, (img_end - img_begin), InputBuf_T::T(1), &(buf[img_begin]));
if (num_bytes == 0) {
ok = lbann::image_utils::import_image(inbuf, width, height, type, pp, Images);
num_bytes = Images.Height();
El::View(Image_v, Images, El::IR(0, num_bytes), El::IR(0, 1));
} else {
El::View(Image_v, Images, El::IR(0, num_bytes), El::IR(0, 1));
//ok = lbann::image_utils::import_image(buf, width, height, type, pp, Image_v);
ok = lbann::image_utils::import_image(inbuf, width, height, type, pp, Image_v);
}
if (!ok) {
std::cout << "Failed to import" << std::endl;
return false;
}
//if ((i%3 == 0u) && (mp.m_enable_mean_extractor)) {
// dynamic_cast<lbann::cv_mean_extractor*>(pp.get_transform(mean_extractor_idx))->reset();
//}
}
// Print out transforms
const unsigned int num_transforms = pp.get_num_transforms();
const std::vector<std::unique_ptr<lbann::cv_transform> >& transforms = pp.get_transforms();
for(unsigned int i=0u; i < num_transforms; ++i) {
std::cout << std::endl << "------------ transform " << i << "-------------" << std::endl;
std::cout << *transforms[i] << std::endl;
}
if (mp.m_enable_mean_extractor) {
// Extract the mean of images
cv::Mat mean_image;
mean_image = dynamic_cast<lbann::cv_mean_extractor*>(pp.get_transform(mean_extractor_idx))->extract<uint16_t>();
cv::imwrite("mean.png", mean_image);
}
// Export the unnormalized image
const std::string ext = lbann::get_ext_name(filename);
std::vector<unsigned char> outbuf;
ok = lbann::image_utils::export_image(ext, outbuf, width, height, type, pp, Image_v);
write_file("copy." + ext, outbuf);
return ok;
}
