1 /**
2 * Copyright 2019 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 #include "minddata/dataset/kernels/image/random_color_adjust_op.h"
17
18 #include <random>
19
20 #include "minddata/dataset/kernels/image/image_utils.h"
21 #include "minddata/dataset/util/random.h"
22 #include "minddata/dataset/util/status.h"
23
24 namespace mindspore {
25 namespace dataset {
RandomColorAdjustOp(float s_bright_factor,float e_bright_factor,float s_contrast_factor,float e_contrast_factor,float s_saturation_factor,float e_saturation_factor,float s_hue_factor,float e_hue_factor)26 RandomColorAdjustOp::RandomColorAdjustOp(float s_bright_factor, float e_bright_factor, float s_contrast_factor,
27 float e_contrast_factor, float s_saturation_factor, float e_saturation_factor,
28 float s_hue_factor, float e_hue_factor)
29 : bright_factor_start_(s_bright_factor),
30 bright_factor_end_(e_bright_factor),
31 contrast_factor_start_(s_contrast_factor),
32 contrast_factor_end_(e_contrast_factor),
33 saturation_factor_start_(s_saturation_factor),
34 saturation_factor_end_(e_saturation_factor),
35 hue_factor_start_(s_hue_factor),
36 hue_factor_end_(e_hue_factor) {
37 rnd_.seed(GetSeed());
38 is_deterministic_ = false;
39 }
40
Compute(const std::shared_ptr<Tensor> & input,std::shared_ptr<Tensor> * output)41 Status RandomColorAdjustOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) {
42 IO_CHECK(input, output);
43
44 // randomly select an augmentation to apply to the input image until all the transformations run
45 std::vector<std::string> params_vector = {"brightness", "contrast", "saturation", "hue"};
46
47 std::shuffle(params_vector.begin(), params_vector.end(), rnd_);
48
49 *output = std::static_pointer_cast<Tensor>(input);
50 // determine if certain augmentation needs to be executed:
51 for (const auto ¶m : params_vector) {
52 // case switch
53 if (param == "brightness") {
54 if (CmpFloat(bright_factor_start_, bright_factor_end_) && CmpFloat(bright_factor_start_, 1.0f)) {
55 MS_LOG(DEBUG) << "Not running brightness.";
56 } else {
57 // adjust the brightness of an image
58 float random_factor = std::uniform_real_distribution<float>(bright_factor_start_, bright_factor_end_)(rnd_);
59 RETURN_IF_NOT_OK(AdjustBrightness(*output, output, random_factor));
60 }
61 } else if (param == "contrast") {
62 if (CmpFloat(contrast_factor_start_, contrast_factor_end_) && CmpFloat(contrast_factor_start_, 1.0f)) {
63 MS_LOG(DEBUG) << "Not running contrast.";
64 } else {
65 float random_factor = std::uniform_real_distribution<float>(contrast_factor_start_, contrast_factor_end_)(rnd_);
66 RETURN_IF_NOT_OK(AdjustContrast(*output, output, random_factor));
67 }
68 } else if (param == "saturation") {
69 // adjust the Saturation of an image
70 if (CmpFloat(saturation_factor_start_, saturation_factor_end_) && CmpFloat(saturation_factor_start_, 1.0f)) {
71 MS_LOG(DEBUG) << "Not running saturation.";
72 } else {
73 float random_factor =
74 std::uniform_real_distribution<float>(saturation_factor_start_, saturation_factor_end_)(rnd_);
75 RETURN_IF_NOT_OK(AdjustSaturation(*output, output, random_factor));
76 }
77 } else if (param == "hue") {
78 if (CmpFloat(hue_factor_start_, hue_factor_end_) && CmpFloat(hue_factor_start_, 0.0f)) {
79 MS_LOG(DEBUG) << "Not running hue.";
80 } else {
81 // adjust the Hue of an image
82 float random_factor = std::uniform_real_distribution<float>(hue_factor_start_, hue_factor_end_)(rnd_);
83 RETURN_IF_NOT_OK(AdjustHue(*output, output, random_factor));
84 }
85 }
86 }
87 // now after we do all the transformations, the last one is fine
88 return Status::OK();
89 }
90 } // namespace dataset
91 } // namespace mindspore
92