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reduced usage of magic numbers #16

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reduced usage of magic numbers #16

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4 changes: 2 additions & 2 deletions scan/frame.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -23,8 +23,8 @@

DMZ_INTERNAL void scan_card_image(IplImage *y, bool collect_card_number, bool scan_expiry, FrameScanResult *result) {
assert(NULL == y->roi);
assert(y->width == 428);
assert(y->height == 270);
assert(y->width == kCreditCardTargetWidth);
assert(y->height == kCreditCardTargetHeight);
assert(y->depth == IPL_DEPTH_8U);
assert(y->nChannels == 1);

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4 changes: 2 additions & 2 deletions scan/n_categorize.cpp
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Expand Up @@ -17,7 +17,7 @@
#include "models/generated/modelc_b00bf70c.hpp"

// TODO: gpu for matrix mult?

#include "dmz_constants.h"

typedef Eigen::Matrix<float, 27, 19, Eigen::RowMajor> NumberImage;
typedef Eigen::Matrix<float, 1, 10, Eigen::RowMajor> SingleNumberScores;
Expand Down Expand Up @@ -81,7 +81,7 @@ DMZ_INTERNAL NumberScores number_scores(IplImage *y_strip, NHorizontalSegmentati
uint16_t y_offset = 0;
if(NULL != y_strip->roi) {
y_offset = (uint16_t)y_strip->roi->yOffset;
assert(y_strip->roi->width == 428);
assert(y_strip->roi->width == kCreditCardTargetWidth);
assert(y_strip->roi->xOffset == 0);
}

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11 changes: 6 additions & 5 deletions scan/n_hseg.cpp
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Expand Up @@ -11,6 +11,7 @@
#include "cv/image_util.h"
#include "cv/morph.h"
#include "opencv2/imgproc/imgproc_c.h"
#include "dmz_constants.h"

static float number_grad_sum_pattern[19] = {
0.26228655f, 0.30289554f, 0.34632607f, 0.38725636f, 0.42745813f, 0.45875135f,
Expand All @@ -33,7 +34,7 @@ typedef struct {

#define SliceU16_MAX UINT16_MAX

typedef Eigen::Matrix<float, 1, 428, Eigen::RowMajor> HorizontalStripPattern;
typedef Eigen::Matrix<float, 1, kCreditCardTargetWidth, Eigen::RowMajor> HorizontalStripPattern;
typedef Eigen::Matrix<float, 1, 19, Eigen::RowMajor> NumberGradSumPattern;

DMZ_INTERNAL NHorizontalSegmentation best_n_hseg_constrained(float *grad_sums, NVerticalSegmentation vseg, NHorizontalSegmentation best, SliceF32 width_slice, SliceU16 offset_slice) {
Expand All @@ -46,7 +47,7 @@ DMZ_INTERNAL NHorizontalSegmentation best_n_hseg_constrained(float *grad_sums, N
for(float width = width_slice.min; width < width_slice.max; width += width_slice.step) {
float pattern_width = vseg.number_pattern_length * width;
uint16_t pattern_offset_max = offset_slice.max;
uint16_t maximum_pattern_offset_max = (uint16_t)(428 - lrintf(pattern_width));
uint16_t maximum_pattern_offset_max = (uint16_t)(kCreditCardTargetWidth - lrintf(pattern_width));
if(pattern_offset_max == SliceU16_MAX || pattern_offset_max > maximum_pattern_offset_max) {
pattern_offset_max = maximum_pattern_offset_max;
}
Expand All @@ -57,7 +58,7 @@ DMZ_INTERNAL NHorizontalSegmentation best_n_hseg_constrained(float *grad_sums, N
for(uint8_t pattern_index = 0; pattern_index < vseg.number_pattern_length; pattern_index++) {
if(vseg.number_pattern[pattern_index]) {
uint16_t center_of_number = (uint16_t)(offset + lrintf(pattern_index * width));
if(center_of_number + 19 < 428) { // shouldn't need this check, just being defensive
if(center_of_number + 19 < kCreditCardTargetWidth) { // shouldn't need this check, just being defensive
pattern.segment<19>(center_of_number) = number_grad_sum_pattern_array;
} else {
in_bounds = false;
Expand Down Expand Up @@ -87,11 +88,11 @@ DMZ_INTERNAL NHorizontalSegmentation best_n_hseg_constrained(float *grad_sums, N

DMZ_INTERNAL NHorizontalSegmentation best_n_hseg(IplImage *y_strip, NVerticalSegmentation vseg) {
// Gradient
IplImage *grad = cvCreateImage(cvSize(428, 27), IPL_DEPTH_8U, 1);
IplImage *grad = cvCreateImage(cvSize(kCreditCardTargetWidth, 27), IPL_DEPTH_8U, 1);
llcv_morph_grad3_2d_cross_u8(y_strip, grad);

// Reduce (sum), normalize
IplImage *grad_sum = cvCreateImage(cvSize(428, 1), IPL_DEPTH_32F, 1); // could sum to IPL_DEPTH_16U and then convert to 32F for normalization, doing it this way for simplicity, will probably get changed during optimization
IplImage *grad_sum = cvCreateImage(cvSize(kCreditCardTargetWidth, 1), IPL_DEPTH_32F, 1); // could sum to IPL_DEPTH_16U and then convert to 32F for normalization, doing it this way for simplicity, will probably get changed during optimization
cvReduce(grad, grad_sum, 0 /* reduce to single row */, CV_REDUCE_SUM);
cvNormalize(grad_sum, grad_sum, 0.0f, 1.0f, CV_MINMAX, NULL);

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12 changes: 6 additions & 6 deletions scan/n_vseg.cpp
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Expand Up @@ -60,7 +60,7 @@ DMZ_INTERNAL inline void best_segmentation_for_vseg_scores(float *visalike_score
best->pattern_type = NumberPatternUnknown;
best->y_offset = 0;

for(uint16_t y_offset = 0; y_offset < 270; y_offset++) {
for(uint16_t y_offset = 0; y_offset < kCreditCardTargetHeight; y_offset++) {
float visalike_score = visalike_scores[y_offset];
float amexlike_score = amexlike_scores[y_offset];

Expand Down Expand Up @@ -106,14 +106,14 @@ DMZ_INTERNAL NVerticalSegmentation best_n_vseg(IplImage *y) {
IplImage *as_float = cvCreateImage(cvSize(204, 1), IPL_DEPTH_32F, 1);

// Score buffers, to be filled in as needed
float visalike_scores[270];
float visalike_scores[kCreditCardTargetHeight];
memset(visalike_scores, 0, sizeof(visalike_scores));

float amexlike_scores[270];
float amexlike_scores[kCreditCardTargetHeight];
memset(amexlike_scores, 0, sizeof(amexlike_scores));

uint16_t min_y_offset = 0;
uint16_t max_y_offset = 270;
uint16_t max_y_offset = kCreditCardTargetHeight;
uint8_t y_offset_step = 4;

// Initially, calculate every fourth score, to narrow down the area in which we have to work
Expand All @@ -137,8 +137,8 @@ DMZ_INTERNAL NVerticalSegmentation best_n_vseg(IplImage *y) {
// whether it is actually a credit card present or not

// All values must be bounds checked against 270 and (when needed) safely against 0 (using uints!)
min_y_offset = MIN(270, best.y_offset < kFineTuningBuffer ? 0 : best.y_offset - kFineTuningBuffer);
max_y_offset = MIN(270, best.y_offset + kVertSegSumWindowSize + kFineTuningBuffer);
min_y_offset = MIN(kCreditCardTargetHeight, best.y_offset < kFineTuningBuffer ? 0 : best.y_offset - kFineTuningBuffer);
max_y_offset = MIN(kCreditCardTargetHeight, best.y_offset + kVertSegSumWindowSize + kFineTuningBuffer);
y_offset_step = 1;

for(uint16_t y_offset = min_y_offset; y_offset < max_y_offset; y_offset += y_offset_step) {
Expand Down