69 lines
2.5 KiB
C
69 lines
2.5 KiB
C
/* Copyright 2023 The MediaPipe Authors.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 MEDIAPIPE_TASKS_C_COMPONENTS_CONTAINERS_CLASSIFICATION_RESULT_H_
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#define MEDIAPIPE_TASKS_C_COMPONENTS_CONTAINERS_CLASSIFICATION_RESULT_H_
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#include <stdbool.h>
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#include <stdint.h>
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#ifdef __cplusplus
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extern "C" {
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#endif
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// Defines classification results for a given classifier head.
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struct Classifications {
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// The array of predicted categories, usually sorted by descending scores,
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// e.g. from high to low probability.
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struct Category* categories;
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// The number of elements in the categories array.
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uint32_t categories_count;
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// The index of the classifier head (i.e. output tensor) these categories
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// refer to. This is useful for multi-head models.
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int head_index;
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// The optional name of the classifier head, as provided in the TFLite Model
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// Metadata [1] if present. This is useful for multi-head models.
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//
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// [1]: https://www.tensorflow.org/lite/convert/metadata
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char* head_name;
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};
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// Defines classification results of a model.
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struct ClassificationResult {
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// The classification results for each head of the model.
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struct Classifications* classifications;
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// The number of classifications in the classifications array.
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uint32_t classifications_count;
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// The optional timestamp (in milliseconds) of the start of the chunk of data
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// corresponding to these results.
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//
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// This is only used for classification on time series (e.g. audio
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// classification). In these use cases, the amount of data to process might
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// exceed the maximum size that the model can process: to solve this, the
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// input data is split into multiple chunks starting at different timestamps.
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int64_t timestamp_ms;
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// Specifies whether the timestamp contains a valid value.
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bool has_timestamp_ms;
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};
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#ifdef __cplusplus
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} // extern C
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#endif
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#endif // MEDIAPIPE_TASKS_C_COMPONENTS_CONTAINERS_CLASSIFICATION_RESULT_H_
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