!5030 Adding a BBox class and fixing Posterize C Op testing.
Merge pull request !5030 from islam_amin/bbox_classpull/5030/MERGE
mindspore-ci-bot
5 years ago
committed by
Gitee
commit
e4d2f2fd3b
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "minddata/dataset/kernels/image/bounding_box.h"
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#include <algorithm>
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#include <vector>
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namespace mindspore {
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namespace dataset {
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const uint8_t kNumOfCols = 4;
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BoundingBox::BoundingBox(bbox_float x, bbox_float y, bbox_float width, bbox_float height)
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: x_(x), y_(y), width_(width), height_(height) {}
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Status BoundingBox::ReadFromTensor(const TensorPtr &bbox_tensor, dsize_t index_of_bbox,
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std::shared_ptr<BoundingBox> *bbox_out) {
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bbox_float x;
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bbox_float y;
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bbox_float width;
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bbox_float height;
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RETURN_IF_NOT_OK(bbox_tensor->GetItemAt<bbox_float>(&x, {index_of_bbox, 0}));
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RETURN_IF_NOT_OK(bbox_tensor->GetItemAt<bbox_float>(&y, {index_of_bbox, 1}));
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RETURN_IF_NOT_OK(bbox_tensor->GetItemAt<bbox_float>(&width, {index_of_bbox, 2}));
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RETURN_IF_NOT_OK(bbox_tensor->GetItemAt<bbox_float>(&height, {index_of_bbox, 3}));
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*bbox_out = std::make_shared<BoundingBox>(x, y, width, height);
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return Status::OK();
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}
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Status BoundingBox::ValidateBoundingBoxes(const TensorRow &image_and_bbox) {
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if (image_and_bbox.size() != 2) {
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return Status(StatusCode::kBoundingBoxInvalidShape, __LINE__, __FILE__,
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"Requires Image and Bounding Boxes, likely missed bounding boxes.");
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}
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if (image_and_bbox[1]->shape().Size() < 2) {
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return Status(StatusCode::kBoundingBoxInvalidShape, __LINE__, __FILE__,
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"Bounding boxes shape should have at least two dimensions.");
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}
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uint32_t num_of_features = image_and_bbox[1]->shape()[1];
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if (num_of_features < 4) {
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return Status(StatusCode::kBoundingBoxInvalidShape, __LINE__, __FILE__,
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"Bounding boxes should be have at least 4 features.");
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}
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std::vector<std::shared_ptr<BoundingBox>> bbox_list;
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RETURN_IF_NOT_OK(GetListOfBoundingBoxes(image_and_bbox[1], &bbox_list));
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uint32_t img_h = image_and_bbox[0]->shape()[0];
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uint32_t img_w = image_and_bbox[0]->shape()[1];
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for (auto &bbox : bbox_list) {
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if ((bbox->x() + bbox->width() > img_w) || (bbox->y() + bbox->height() > img_h)) {
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return Status(StatusCode::kBoundingBoxOutOfBounds, __LINE__, __FILE__,
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"At least one of the bounding boxes is out of bounds of the image.");
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}
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if (static_cast<int>(bbox->x()) < 0 || static_cast<int>(bbox->y()) < 0) {
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return Status(StatusCode::kBoundingBoxOutOfBounds, __LINE__, __FILE__,
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"At least one of the bounding boxes has negative min_x or min_y.");
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}
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}
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return Status::OK();
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}
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Status BoundingBox::WriteToTensor(const TensorPtr &bbox_tensor, dsize_t index_of_bbox) {
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RETURN_IF_NOT_OK(bbox_tensor->SetItemAt<bbox_float>({index_of_bbox, 0}, x_));
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RETURN_IF_NOT_OK(bbox_tensor->SetItemAt<bbox_float>({index_of_bbox, 1}, y_));
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RETURN_IF_NOT_OK(bbox_tensor->SetItemAt<bbox_float>({index_of_bbox, 2}, width_));
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RETURN_IF_NOT_OK(bbox_tensor->SetItemAt<bbox_float>({index_of_bbox, 3}, height_));
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return Status::OK();
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}
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Status BoundingBox::GetListOfBoundingBoxes(const TensorPtr &bbox_tensor,
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std::vector<std::shared_ptr<BoundingBox>> *bbox_out) {
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dsize_t num_of_boxes = bbox_tensor->shape()[0];
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for (dsize_t i = 0; i < num_of_boxes; i++) {
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std::shared_ptr<BoundingBox> bbox;
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RETURN_IF_NOT_OK(ReadFromTensor(bbox_tensor, i, &bbox));
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bbox_out->push_back(bbox);
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}
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return Status::OK();
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}
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Status BoundingBox::CreateTensorFromBoundingBoxList(const std::vector<std::shared_ptr<BoundingBox>> &bboxes,
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TensorPtr *tensor_out) {
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dsize_t num_of_boxes = bboxes.size();
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std::vector<bbox_float> bboxes_for_tensor;
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for (dsize_t i = 0; i < num_of_boxes; i++) {
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bbox_float b_data[kNumOfCols] = {bboxes[i]->x(), bboxes[i]->y(), bboxes[i]->width(), bboxes[i]->height()};
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bboxes_for_tensor.insert(bboxes_for_tensor.end(), b_data, b_data + kNumOfCols);
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}
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RETURN_IF_NOT_OK(Tensor::CreateFromVector(bboxes_for_tensor, TensorShape{num_of_boxes, kNumOfCols}, tensor_out));
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return Status::OK();
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}
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Status BoundingBox::PadBBoxes(const TensorPtr *bbox_list, size_t bbox_count, int32_t pad_top, int32_t pad_left) {
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for (dsize_t i = 0; i < bbox_count; i++) {
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std::shared_ptr<BoundingBox> bbox;
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RETURN_IF_NOT_OK(ReadFromTensor(*bbox_list, i, &bbox));
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bbox->SetX(bbox->x() + pad_left);
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bbox->SetY(bbox->y() + pad_top);
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RETURN_IF_NOT_OK(bbox->WriteToTensor(*bbox_list, i));
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}
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return Status::OK();
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}
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Status BoundingBox::UpdateBBoxesForCrop(TensorPtr *bbox_list, size_t *bbox_count, int32_t CB_Xmin, int32_t CB_Ymin,
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int32_t CB_Xmax, int32_t CB_Ymax) {
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// PASS LIST, COUNT OF BOUNDING BOXES
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// Also PAss X/Y Min/Max of image cropped region - normally obtained from 'GetCropBox' functions
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std::vector<dsize_t> correct_ind;
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std::vector<bbox_float> copyVals;
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bool retFlag = false; // true unless overlap found
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dsize_t bboxDim = (*bbox_list)->shape()[1];
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for (dsize_t i = 0; i < *bbox_count; i++) {
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std::shared_ptr<BoundingBox> bbox;
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RETURN_IF_NOT_OK(ReadFromTensor(*bbox_list, i, &bbox));
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bbox_float bb_Xmax = bbox->x() + bbox->width();
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bbox_float bb_Ymax = bbox->y() + bbox->height();
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// check for image / BB overlap
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if (((bbox->x() > CB_Xmax) || (bbox->y() > CB_Ymax)) || ((bb_Xmax < CB_Xmin) || (bb_Ymax < CB_Ymin))) {
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continue; // no overlap found
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}
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// Update this bbox and select it to move to the final output tensor
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correct_ind.push_back(i);
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// adjust BBox corners by bringing into new CropBox if beyond
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// Also reseting/adjusting for boxes to lie within CropBox instead of Image - subtract CropBox Xmin/YMin
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bbox_float bb_Xmin = bbox->x() - std::min(static_cast<bbox_float>(0.0), (bbox->x() - CB_Xmin)) - CB_Xmin;
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bbox_float bb_Ymin = bbox->y() - std::min(static_cast<bbox_float>(0.0), (bbox->y() - CB_Ymin)) - CB_Ymin;
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bb_Xmax = bb_Xmax - std::max(static_cast<bbox_float>(0.0), (bb_Xmax - CB_Xmax)) - CB_Xmin;
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bb_Ymax = bb_Ymax - std::max(static_cast<bbox_float>(0.0), (bb_Ymax - CB_Ymax)) - CB_Ymin;
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// bound check for float values
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bb_Xmin = std::max(bb_Xmin, static_cast<bbox_float>(0));
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bb_Ymin = std::max(bb_Ymin, static_cast<bbox_float>(0));
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bb_Xmax = std::min(bb_Xmax, static_cast<bbox_float>(CB_Xmax - CB_Xmin)); // find max value relative to new image
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bb_Ymax = std::min(bb_Ymax, static_cast<bbox_float>(CB_Ymax - CB_Ymin));
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// reset min values and calculate width/height from Box corners
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bbox->SetX(bb_Xmin);
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bbox->SetY(bb_Ymin);
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bbox->SetWidth(bb_Xmax - bb_Xmin);
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bbox->SetHeight(bb_Ymax - bb_Ymin);
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RETURN_IF_NOT_OK(bbox->WriteToTensor(*bbox_list, i));
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}
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// create new tensor and copy over bboxes still valid to the image
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// bboxes outside of new cropped region are ignored - empty tensor returned in case of none
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*bbox_count = correct_ind.size();
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bbox_float temp = 0.0;
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for (auto slice : correct_ind) { // for every index in the loop
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for (dsize_t ix = 0; ix < bboxDim; ix++) {
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RETURN_IF_NOT_OK((*bbox_list)->GetItemAt<bbox_float>(&temp, {slice, ix}));
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copyVals.push_back(temp);
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}
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}
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std::shared_ptr<Tensor> retV;
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RETURN_IF_NOT_OK(
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Tensor::CreateFromVector(copyVals, TensorShape({static_cast<dsize_t>(*bbox_count), bboxDim}), &retV));
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(*bbox_list) = retV; // reset pointer
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return Status::OK();
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}
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Status BoundingBox::UpdateBBoxesForResize(const TensorPtr &bbox_list, size_t bbox_count, int32_t target_width,
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int32_t target_height, int32_t orig_width, int32_t orig_height) {
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// cast to float to preserve fractional
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bbox_float W_aspRatio = (target_width * 1.0) / (orig_width * 1.0);
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bbox_float H_aspRatio = (target_height * 1.0) / (orig_height * 1.0);
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for (dsize_t i = 0; i < bbox_count; i++) {
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// for each bounding box
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std::shared_ptr<BoundingBox> bbox;
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RETURN_IF_NOT_OK(ReadFromTensor(bbox_list, i, &bbox));
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// update positions and widths
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bbox->SetX(bbox->x() * W_aspRatio);
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bbox->SetY(bbox->y() * H_aspRatio);
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bbox->SetWidth(bbox->width() * W_aspRatio);
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bbox->SetHeight(bbox->height() * H_aspRatio);
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// reset bounding box values
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bbox->WriteToTensor(bbox_list, i);
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}
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return Status::OK();
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}
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} // namespace dataset
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} // namespace mindspore
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@ -0,0 +1,137 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IMAGE_BOUNDING_BOX_H_
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#define MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IMAGE_BOUNDING_BOX_H_
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#include <memory>
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#include <vector>
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#include <string>
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#include "minddata/dataset/core/tensor.h"
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#include "minddata/dataset/core/tensor_row.h"
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#include "minddata/dataset/util/status.h"
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namespace mindspore {
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namespace dataset {
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class BoundingBox {
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public:
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typedef float_t bbox_float;
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/// \brief Constructor for BoundingBox
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/// \param[in] x horizontal axis coordinate of bounding box
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/// \param[in] y vertical axis coordinate of bounding box
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/// \param[in] width width of bounding box on horizontal axis
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/// \param[in] height height of bounding box on vertical axis
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BoundingBox(bbox_float x, bbox_float y, bbox_float width, bbox_float height);
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~BoundingBox() = default;
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/// \brief Provide stream operator for displaying a bounding box.
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friend std::ostream &operator<<(std::ostream &out, const BoundingBox &bbox) {
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out << "Bounding Box with (X,Y,W,H): (" << bbox.x_ << "," << bbox.y_ << "," << bbox.width_ << "," << bbox.height_
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<< ")";
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return out;
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}
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/// Getters
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bbox_float x() { return x_; }
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bbox_float y() { return y_; }
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bbox_float width() { return width_; }
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bbox_float height() { return height_; }
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/// Setters
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void SetX(bbox_float x) { x_ = x; }
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void SetY(bbox_float y) { y_ = y; }
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void SetWidth(bbox_float w) { width_ = w; }
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void SetHeight(bbox_float h) { height_ = h; }
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/// \brief Set the bounding box data to bbox at a certain index in the tensor.
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/// \param[in] bbox_tensor tensor containing a list of bounding boxes of shape (m, n) where n >= 4
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/// and first 4 items of each row are x,y,w,h of the bounding box
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/// \param[in] index_of_bbox index of bounding box to set to tensor
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/// \returns Status status of bounding box set
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Status WriteToTensor(const TensorPtr &bbox_tensor, dsize_t index_of_bbox = 0);
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/// \brief Create a bounding box object from an item at a certain index in a tensor.
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/// \param[in] bbox_tensor tensor containing a list of bounding boxes of shape (m, n) where n >= 4
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/// and first 4 items of each row are x,y,w,h of the bounding box
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/// \param[in] index_of_bbox index of bounding box to fetch from the tensor
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/// \param[out] bbox_out output bounding box
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/// \returns Status status of bounding box fetch
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static Status ReadFromTensor(const TensorPtr &bbox_tensor, dsize_t index_of_bbox,
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std::shared_ptr<BoundingBox> *bbox_out);
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/// \brief Validate a list of bounding boxes with respect to an image.
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/// \param[in] image_and_bbox tensor containing a list of bounding boxes of shape (m, n) where n >= 4
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/// and first 4 items of each row are x,y,w,h of the bounding box and an image of shape (H, W, C) or (H, W)
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/// \returns Status status of bounding box fetch
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static Status ValidateBoundingBoxes(const TensorRow &image_and_bbox);
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/// \brief Get a list of bounding boxes from a tensor.
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/// \param[in] bbox_tensor tensor containing a list of bounding boxes of shape (m, n) where n >= 4
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/// and first 4 items of each row are x,y,w,h of the bounding box
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/// \param[out] bbox_out output vector of bounding boxes
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/// \returns Status status of bounding box list fetch
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static Status GetListOfBoundingBoxes(const TensorPtr &bbox_tensor,
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std::vector<std::shared_ptr<BoundingBox>> *bbox_out);
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/// \brief Creates a tensor from a list of bounding boxes.
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/// \param[in] bboxes list of bounding boxes
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/// \param[out] tensor_out output tensor
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/// \returns Status status of tensor creation
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static Status CreateTensorFromBoundingBoxList(const std::vector<std::shared_ptr<BoundingBox>> &bboxes,
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TensorPtr *tensor_out);
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/// \brief Updates bounding boxes with required Top and Left padding
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/// \note Top and Left padding amounts required to adjust bboxs min X,Y values according to padding 'push'
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/// Top/Left since images 0,0 coordinate is taken from top left
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/// \param bboxList: A tensor contaning bounding box tensors
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/// \param bboxCount: total Number of bounding boxes - required within caller function to run update loop
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/// \param pad_top: Total amount of padding applied to image top
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/// \param pad_left: Total amount of padding applied to image left side
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static Status PadBBoxes(const TensorPtr *bbox_list, size_t bbox_count, int32_t pad_top, int32_t pad_left);
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/// \brief Updates and checks bounding boxes for new cropped region of image
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/// \param bbox_list: A tensor contaning bounding box tensors
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/// \param bbox_count: total Number of bounding boxes - required within caller function to run update loop
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/// \param CB_Xmin: Image's CropBox Xmin coordinate
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/// \param CB_Xmin: Image's CropBox Ymin coordinate
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/// \param CB_Xmax: Image's CropBox Xmax coordinate - (Xmin + width)
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/// \param CB_Xmax: Image's CropBox Ymax coordinate - (Ymin + height)
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static Status UpdateBBoxesForCrop(TensorPtr *bbox_list, size_t *bbox_count, int32_t CB_Xmin, int32_t CB_Ymin,
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int32_t CB_Xmax, int32_t CB_Ymax);
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/// \brief Updates bounding boxes for an Image Resize Operation - Takes in set of valid BBoxes
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/// For e.g those that remain after a crop
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/// \param bbox_list: A tensor contaning bounding box tensors
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/// \param bbox_count: total Number of bounding boxes - required within caller function to run update loop
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/// \param target_width: required width of image post resize
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/// \param target_height: required height of image post resize
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/// \param orig_width: current width of image pre resize
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/// \param orig_height: current height of image pre resize
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static Status UpdateBBoxesForResize(const TensorPtr &bbox_list, size_t bbox_count, int32_t target_width,
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int32_t target_height, int32_t orig_width, int32_t orig_height);
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private:
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bbox_float x_;
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bbox_float y_;
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bbox_float width_;
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bbox_float height_;
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};
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} // namespace dataset
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_MINDDATA_DATASET_KERNELS_IMAGE_BOUNDING_BOX_H_
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