add_multi_label_postprocess (#950)

* 'add_multi_label_postprocess'

* fix pre-commit

* delete partial_sort

* delete idx

* delete num_classes and num_classes_

* Fix right brackets and spelling errors in lines 19 and 20

Co-authored-by: gaoying <gaoying@xiaobaishiji.com>
pull/964/head
gy77 2022-08-30 19:02:42 +08:00 committed by GitHub
parent 13920ec1a2
commit 638e33a964
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// Copyright (c) OpenMMLab. All rights reserved.
#include <algorithm>
#include <numeric>
#include "mmdeploy/codebase/mmcls/mmcls.h"
#include "mmdeploy/core/tensor.h"
#include "mmdeploy/core/utils/device_utils.h"
#include "mmdeploy/core/utils/formatter.h"
#include "mmdeploy/experimental/module_adapter.h"
using std::vector;
namespace mmdeploy::mmcls {
class MultiLabelLinearClsHead : public MMClassification {
public:
explicit MultiLabelLinearClsHead(const Value& cfg) : MMClassification(cfg) {}
Result<Value> operator()(const Value& infer_res) {
MMDEPLOY_DEBUG("infer_res: {}", infer_res);
auto output = infer_res["output"].get<Tensor>();
if (!(output.shape().size() >= 2 && output.data_type() == DataType::kFLOAT)) {
MMDEPLOY_ERROR("unsupported `output` tensor, shape: {}, dtype: {}", output.shape(),
(int)output.data_type());
return Status(eNotSupported);
}
auto class_num = (int)output.shape(1);
OUTCOME_TRY(auto _scores, MakeAvailableOnDevice(output, kHost, stream()));
OUTCOME_TRY(stream().Wait());
return GetLabels(_scores, class_num);
}
private:
Value GetLabels(const Tensor& scores, int class_num) const {
auto scores_data = scores.data<float>();
ClassifyOutput output;
for (int i = 0; i < class_num; ++i) {
auto label = ClassifyOutput::Label{i, scores_data[i]};
MMDEPLOY_DEBUG("label_id: {}, score: {}", label.label_id, label.score);
output.labels.push_back(label);
}
return to_value(std::move(output));
}
private:
static constexpr const auto kHost = Device{0};
};
REGISTER_CODEBASE_COMPONENT(MMClassification, MultiLabelLinearClsHead);
} // namespace mmdeploy::mmcls