TYPED_TEST(DataTransformTest, TestCropSize) {
TransformationParameter transform_param;
const bool unique_pixels = false; // all pixels the same equal to label
const int_tp label = 0;
const int_tp channels = 3;
const int_tp height = 4;
const int_tp width = 5;
const int_tp crop_size = 2;
transform_param.set_crop_size(crop_size);
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST,
Caffe::GetDefaultDevice());
transformer->InitRand();
Blob<TypeParam>* blob =
new Blob<TypeParam>(1, channels, crop_size, crop_size);
for (int_tp iter = 0; iter < this->num_iter_; ++iter) {
transformer->Transform(datum, blob);
EXPECT_EQ(blob->num(), 1);
EXPECT_EQ(blob->channels(), datum.channels());
EXPECT_EQ(blob->height(), crop_size);
EXPECT_EQ(blob->width(), crop_size);
for (int_tp j = 0; j < blob->count(); ++j) {
EXPECT_EQ(blob->cpu_data()[j], label);
}
}
}
TYPED_TEST(DataTransformTest, TestMeanValues) {
TransformationParameter transform_param;
const bool unique_pixels = false; // pixels are equal to label
const int_tp label = 0;
const int_tp channels = 3;
const int_tp height = 4;
const int_tp width = 5;
transform_param.add_mean_value(0);
transform_param.add_mean_value(1);
transform_param.add_mean_value(2);
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
Blob<TypeParam>* blob = new Blob<TypeParam>(1, channels, height, width);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST,
Caffe::GetDefaultDevice());
transformer->InitRand();
transformer->Transform(datum, blob);
for (int_tp c = 0; c < channels; ++c) {
for (int_tp j = 0; j < height * width; ++j) {
EXPECT_EQ(blob->cpu_data()[blob->offset(0, c) + j], label - c);
}
}
}
std::string encodeForSaving(const char* value, const char* user_token)
{
std::string res("");
if ((user_token != NULL) && (strlen(user_token) > 0)) {
if (value == NULL || strlen(value) == 0) {
return res;
}
DataTransformer* enc = DataTransformerFactory::getEncoder(DT_DES);
TransformationInfo info;
info.size = (long)strlen(value)*sizeof(char);
info.password = user_token;
char* v = strdup(value);
char* desValue = enc->transform(v, info);
DataTransformer* b64Enc = DataTransformerFactory::getEncoder(DT_B64);
char* b64Value = b64Enc->transform(desValue, info);
free(v);
if (desValue) {
free(desValue);
}
res = b64Value;
delete [] b64Value;
} else {
res = value;
}
return res;
}
USE_NAMESPACE
//
// IMPORTANT: this test case encodes/decodes a UNICODE string; make sure
// to update it to UTF8 strings when used with such content.
//
void testEncryption() {
char* clearText = "This is clear text.\nLet's see if encryption/decryption works!";
char* password = "******";
DataTransformer* b64e = DataTransformerFactory::getEncoder("b64");
DataTransformer* b64d = DataTransformerFactory::getDecoder("b64");
DataTransformer* dese = DataTransformerFactory::getEncoder("des");
DataTransformer* desd = DataTransformerFactory::getDecoder("des");
TransformationInfo infoe, infod;
infoe.size = strlen(clearText)*sizeof(char);
infoe.password = password;
LOG.info("Clear text");
LOG.info("%s", clearText);
char* desText = dese->transform(clearText, infoe);
char* b64Text = b64e->transform(desText, infoe);
LOG.info("Clear text");
LOG.info("%s", b64Text);
delete [] desText;
infod.size = infoe.size;
infod.password = infoe.password;
desText = b64d->transform(b64Text, infod);
clearText = desd->transform(desText, infod);
char* clearString = new char[infod.size/sizeof(char)+1];
strncpy(clearString, clearText, infod.size/sizeof(char));
clearString[infod.size/sizeof(char)] = 0;
LOG.info("Clear text");
LOG.info("%s", clearString);
delete [] clearString; delete [] clearText;
delete [] b64Text; delete [] desText;
}
TYPED_TEST(DataTransformTest, TestMeanValue) {
TransformationParameter transform_param;
const bool unique_pixels = false; // pixels are equal to label
const int label = 0;
const int channels = 3;
const int height = 4;
const int width = 5;
const int mean_value = 2;
transform_param.add_mean_value(mean_value);
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
Blob<TypeParam>* blob = new Blob<TypeParam>(1, channels, height, width);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST);
transformer->InitRand();
transformer->Transform(datum, blob);
for (int j = 0; j < blob->count(); ++j) {
EXPECT_EQ(blob->cpu_data()[j], label - mean_value);
}
}
int NumSequenceMatches(const TransformationParameter transform_param,
const Datum& datum, Phase phase) {
// Get crop sequence with Caffe seed 1701.
DataTransformer<Dtype>* transformer =
new DataTransformer<Dtype>(transform_param, phase);
const int crop_size = transform_param.crop_size();
int crop_h = transform_param.crop_h();
int crop_w = transform_param.crop_w();
if (crop_size > 0) {
crop_h = crop_w = crop_size;
}
Caffe::set_random_seed(seed_);
transformer->InitRand();
Blob<Dtype>* blob =
new Blob<Dtype>(1, datum.channels(), datum.height(), datum.width());
if (crop_h > 0 || crop_w > 0) {
blob->Reshape(1, datum.channels(), crop_h, crop_w);
}
vector<vector<Dtype> > crop_sequence;
for (int iter = 0; iter < this->num_iter_; ++iter) {
vector<Dtype> iter_crop_sequence;
transformer->Transform(datum, blob);
for (int j = 0; j < blob->count(); ++j) {
iter_crop_sequence.push_back(blob->cpu_data()[j]);
}
crop_sequence.push_back(iter_crop_sequence);
}
// Check if the sequence differs from the previous
int num_sequence_matches = 0;
for (int iter = 0; iter < this->num_iter_; ++iter) {
vector<Dtype> iter_crop_sequence = crop_sequence[iter];
transformer->Transform(datum, blob);
for (int j = 0; j < blob->count(); ++j) {
num_sequence_matches +=
(crop_sequence[iter][j] == blob->cpu_data()[j]);
}
}
return num_sequence_matches;
}
TYPED_TEST(DataTransformTest, TestMeanFile) {
TransformationParameter transform_param;
const bool unique_pixels = true; // pixels are consecutive ints [0,size]
const int_tp label = 0;
const int_tp channels = 3;
const int_tp height = 4;
const int_tp width = 5;
const int_tp size = channels * height * width;
// Create a mean file
string* mean_file = new string();
MakeTempFilename(mean_file);
BlobProto blob_mean;
blob_mean.set_num(1);
blob_mean.set_channels(channels);
blob_mean.set_height(height);
blob_mean.set_width(width);
for (int_tp j = 0; j < size; ++j) {
blob_mean.add_data(j);
}
LOG(INFO) << "Using temporary mean_file " << *mean_file;
WriteProtoToBinaryFile(blob_mean, *mean_file);
transform_param.set_mean_file(*mean_file);
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
Blob<TypeParam>* blob = new Blob<TypeParam>(1, channels, height, width);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST,
Caffe::GetDefaultDevice());
transformer->InitRand();
transformer->Transform(datum, blob);
for (int_tp j = 0; j < blob->count(); ++j) {
EXPECT_EQ(blob->cpu_data()[j], 0);
}
}
TYPED_TEST(DataTransformTest, TestEmptyTransform) {
TransformationParameter transform_param;
const bool unique_pixels = false; // all pixels the same equal to label
const int label = 0;
const int channels = 3;
const int height = 4;
const int width = 5;
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
Blob<TypeParam>* blob = new Blob<TypeParam>(1, channels, height, width);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST);
transformer->InitRand();
transformer->Transform(datum, blob);
EXPECT_EQ(blob->num(), 1);
EXPECT_EQ(blob->channels(), datum.channels());
EXPECT_EQ(blob->height(), datum.height());
EXPECT_EQ(blob->width(), datum.width());
for (int j = 0; j < blob->count(); ++j) {
EXPECT_EQ(blob->cpu_data()[j], label);
}
}
TYPED_TEST(DataTransformTest, TestEmptyTransformUniquePixels) {
TransformationParameter transform_param;
const bool unique_pixels = true; // pixels are consecutive ints [0,size]
const int label = 0;
const int channels = 3;
const int height = 4;
const int width = 5;
Datum datum;
FillDatum(label, channels, height, width, unique_pixels, &datum);
Blob<TypeParam>* blob = new Blob<TypeParam>(1, 3, 4, 5);
DataTransformer<TypeParam>* transformer =
new DataTransformer<TypeParam>(transform_param, TEST);
transformer->InitRand();
transformer->Transform(datum, blob);
EXPECT_EQ(blob->num(), 1);
EXPECT_EQ(blob->channels(), datum.channels());
EXPECT_EQ(blob->height(), datum.height());
EXPECT_EQ(blob->width(), datum.width());
for (int j = 0; j < blob->count(); ++j) {
EXPECT_EQ(blob->cpu_data()[j], j);
}
}
std::string decodeAfterReading(const char *value, const char* user_token)
{
std::string res(value);
if ((user_token != NULL) && (strlen(user_token) > 0)) {
if (value == NULL || strlen(value) == 0) {
return "";
}
// Password is stored as b64(des(password))
DataTransformer* b64Dec = DataTransformerFactory::getDecoder(DT_B64);
TransformationInfo info;
char* v = strdup(value);
info.size = (long)strlen(v)*sizeof(char);
char* b64DecValue = b64Dec->transform(v, info);
DataTransformer* dec = DataTransformerFactory::getDecoder(DT_DES);
info.password = user_token;
char* desValue = dec->transform(b64DecValue, info);
if (desValue != NULL && info.size > 0) {
desValue[info.size] = 0;
}
free(v);
if (desValue != NULL) {
res = desValue;
}
delete [] b64DecValue;
if (info.newReturnedData == true) {
delete [] desValue;
}
}
return res;
}
