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Debt Task

This commit is contained in:
Danish Farid 2020-07-03 13:42:11 -04:00
parent 7cc4b8438e
commit e8f879aa43
1 changed files with 22 additions and 12 deletions
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34
mindspore/ccsrc/dataset/kernels/image/image_utils.cc
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@ -108,7 +108,8 @@ Status Resize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *out
} }
try { try {
TensorShape shape{output_height, output_width}; TensorShape shape{output_height, output_width};
if (input_cv->Rank() == 3) shape = shape.AppendDim(input_cv->shape()[2]); int num_channels = input_cv->shape()[2];
if (input_cv->Rank() == 3) shape = shape.AppendDim(num_channels);
std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(shape, input_cv->type()); std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(shape, input_cv->type());
RETURN_UNEXPECTED_IF_NULL(output_cv); RETURN_UNEXPECTED_IF_NULL(output_cv);
auto cv_mode = GetCVInterpolationMode(mode); auto cv_mode = GetCVInterpolationMode(mode);
@ -351,7 +352,8 @@ Status Crop(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *outpu
} }
try { try {
TensorShape shape{h, w}; TensorShape shape{h, w};
if (input_cv->Rank() == 3) shape = shape.AppendDim(input_cv->shape()[2]); int num_channels = input_cv->shape()[2];
if (input_cv->Rank() == 3) shape = shape.AppendDim(num_channels);
std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(shape, input_cv->type()); std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(shape, input_cv->type());
RETURN_UNEXPECTED_IF_NULL(output_cv); RETURN_UNEXPECTED_IF_NULL(output_cv);
cv::Rect roi(x, y, w, h); cv::Rect roi(x, y, w, h);
@ -374,15 +376,15 @@ Status HwcToChw(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output)
*output = input; *output = input;
return Status::OK(); return Status::OK();
} }
int num_channels = input_cv->shape()[2];
if (input_cv->shape().Size() < 2 || input_cv->shape().Size() > 3 || if (input_cv->shape().Size() < 2 || input_cv->shape().Size() > 3 ||
(input_cv->shape().Size() == 3 && input_cv->shape()[2] != 3 && input_cv->shape()[2] != 1)) { (input_cv->shape().Size() == 3 && num_channels != 3 && num_channels != 1)) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3 nor 1"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3 nor 1");
} }
cv::Mat output_img; cv::Mat output_img;
int height = input_cv->shape()[0]; int height = input_cv->shape()[0];
int width = input_cv->shape()[1]; int width = input_cv->shape()[1];
int num_channels = input_cv->shape()[2];
auto output_cv = std::make_unique<CVTensor>(TensorShape{num_channels, height, width}, input_cv->type()); auto output_cv = std::make_unique<CVTensor>(TensorShape{num_channels, height, width}, input_cv->type());
for (int i = 0; i < num_channels; ++i) { for (int i = 0; i < num_channels; ++i) {
@ -400,7 +402,8 @@ Status HwcToChw(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output)
Status SwapRedAndBlue(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output) { Status SwapRedAndBlue(std::shared_ptr<Tensor> input, std::shared_ptr<Tensor> *output) {
try { try {
std::shared_ptr<CVTensor> input_cv = CVTensor::AsCVTensor(std::move(input)); std::shared_ptr<CVTensor> input_cv = CVTensor::AsCVTensor(std::move(input));
if (input_cv->shape().Size() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->shape().Size() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3");
} }
auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type()); auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type());
@ -435,7 +438,8 @@ Status CropAndResize(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tenso
auto cv_mode = GetCVInterpolationMode(mode); auto cv_mode = GetCVInterpolationMode(mode);
cv::Mat cv_in = input_cv->mat(); cv::Mat cv_in = input_cv->mat();
TensorShape shape{target_height, target_width}; TensorShape shape{target_height, target_width};
if (input_cv->Rank() == 3) shape = shape.AppendDim(input_cv->shape()[2]); int num_channels = input_cv->shape()[2];
if (input_cv->Rank() == 3) shape = shape.AppendDim(num_channels);
std::shared_ptr<CVTensor> cvt_out = std::make_shared<CVTensor>(shape, input_cv->type()); std::shared_ptr<CVTensor> cvt_out = std::make_shared<CVTensor>(shape, input_cv->type());
RETURN_UNEXPECTED_IF_NULL(cvt_out); RETURN_UNEXPECTED_IF_NULL(cvt_out);
cv::resize(cv_in(roi), cvt_out->mat(), cv::Size(target_width, target_height), 0, 0, cv_mode); cv::resize(cv_in(roi), cvt_out->mat(), cv::Size(target_width, target_height), 0, 0, cv_mode);
@ -540,7 +544,8 @@ Status AdjustBrightness(const std::shared_ptr<Tensor> &input, std::shared_ptr<Te
if (!input_cv->mat().data) { if (!input_cv->mat().data) {
RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor"); RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor");
} }
if (input_cv->Rank() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->Rank() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3");
} }
auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type()); auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type());
@ -560,7 +565,8 @@ Status AdjustContrast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tens
if (!input_cv->mat().data) { if (!input_cv->mat().data) {
RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor"); RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor");
} }
if (input_cv->Rank() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->Rank() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3");
} }
cv::Mat gray, output_img; cv::Mat gray, output_img;
@ -586,7 +592,8 @@ Status AdjustSaturation(const std::shared_ptr<Tensor> &input, std::shared_ptr<Te
if (!input_cv->mat().data) { if (!input_cv->mat().data) {
RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor"); RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor");
} }
if (input_cv->Rank() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->Rank() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3");
} }
auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type()); auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type());
@ -614,7 +621,8 @@ Status AdjustHue(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *
if (!input_cv->mat().data) { if (!input_cv->mat().data) {
RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor"); RETURN_STATUS_UNEXPECTED("Could not convert to CV Tensor");
} }
if (input_cv->Rank() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->Rank() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3"); RETURN_STATUS_UNEXPECTED("The shape is incorrect: number of channels does not equal 3");
} }
auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type()); auto output_cv = std::make_shared<CVTensor>(input_cv->shape(), input_cv->type());
@ -643,7 +651,8 @@ Status Erase(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *outp
uint8_t fill_g, uint8_t fill_b) { uint8_t fill_g, uint8_t fill_b) {
try { try {
std::shared_ptr<CVTensor> input_cv = CVTensor::AsCVTensor(input); std::shared_ptr<CVTensor> input_cv = CVTensor::AsCVTensor(input);
if (input_cv->mat().data == nullptr || input_cv->Rank() != 3 || input_cv->shape()[2] != 3) { int num_channels = input_cv->shape()[2];
if (input_cv->mat().data == nullptr || input_cv->Rank() != 3 || num_channels != 3) {
RETURN_STATUS_UNEXPECTED("bad CV Tensor input for erase"); RETURN_STATUS_UNEXPECTED("bad CV Tensor input for erase");
} }
cv::Mat input_img = input_cv->mat(); cv::Mat input_img = input_cv->mat();
@ -717,7 +726,8 @@ Status Pad(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output
std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(out_image); std::shared_ptr<CVTensor> output_cv = std::make_shared<CVTensor>(out_image);
RETURN_UNEXPECTED_IF_NULL(output_cv); RETURN_UNEXPECTED_IF_NULL(output_cv);
// pad the dimension if shape information is only 2 dimensional, this is grayscale // pad the dimension if shape information is only 2 dimensional, this is grayscale
if (input_cv->Rank() == 3 && input_cv->shape()[2] == 1 && output_cv->Rank() == 2) output_cv->ExpandDim(2); int num_channels = input_cv->shape()[2];
if (input_cv->Rank() == 3 && num_channels == 1 && output_cv->Rank() == 2) output_cv->ExpandDim(2);
*output = std::static_pointer_cast<Tensor>(output_cv); *output = std::static_pointer_cast<Tensor>(output_cv);
return Status::OK(); return Status::OK();