int mv_image_classification_inference_async(mv_image_classification_h handle, mv_source_h source);
/**
- * @brief Gets the label value as a image classification inference result.
- * @details Use this function to get the label value after calling @ref mv_image_classification_inference().
- *
- * @since_tizen 9.0
- *
- * @remarks The @a result must NOT be released using free()
- *
- * @param[in] handle The handle to the image classification object.
- * @param[out] out_label A pointer to the label string.
- *
- * @return @c 0 on success, otherwise a negative error value
- * @retval #MEDIA_VISION_ERROR_NONE Successful
- * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
- * @retval #MEDIA_VISION_ERROR_INVALID_OPERATION Invalid operation
- *
- * @pre Request an inference by calling @ref mv_image_classification_inference()
- */
-int mv_image_classification_get_label(mv_image_classification_h handle, const char **out_label);
+ * @internal
+ * @brief Gets the image classification inference result count on the @a source.
+ *
+ * @since_tizen 9.0
+ *
+ * @param[in] handle The handle to the inference
+ * @param[out] result_cnt A number of results.
+ *
+ * @return @c 0 on success, otherwise a negative error value
+ * @retval #MEDIA_VISION_ERROR_NONE Successful
+ * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
+ * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
+ * @retval #MEDIA_VISION_ERROR_INTERNAL Internal error
+ *
+ * @pre Create a source handle by calling mv_create_source()
+ * @pre Create an inference handle by calling mv_image_classification_create()
+ * @pre Prepare an inference by calling mv_image_classification_configure()
+ * @pre Prepare an inference by calling mv_image_classification_prepare()
+ * @pre Request an inference by calling mv_image_classification_inference()
+ */
+int mv_image_classification_get_result_count(mv_image_classification_h handle, unsigned int *result_cnt);
+
+/**
+ * @internal
+ * @brief Gets the image classification inference result to a given index.
+ *
+ * @since_tizen 9.0
+ *
+ * @param[in] handle The handle to the inference
+ * @param[in] index A result index.
+ * @param[out] frame_number A frame number inferenced.
+ * @param[out] label A label name to a detected object.
+ *
+ * @return @c 0 on success, otherwise a negative error value
+ * @retval #MEDIA_VISION_ERROR_NONE Successful
+ * @retval #MEDIA_VISION_ERROR_NOT_SUPPORTED Not supported
+ * @retval #MEDIA_VISION_ERROR_INVALID_PARAMETER Invalid parameter
+ * @retval #MEDIA_VISION_ERROR_INTERNAL Internal error
+ *
+ * @pre Create a source handle by calling mv_create_source()
+ * @pre Create an inference handle by calling mv_image_classification_create()
+ * @pre Prepare an inference by calling mv_image_classification_configure()
+ * @pre Prepare an inference by calling mv_image_classification_prepare()
+ * @pre Request an inference by calling mv_image_classification_inference()
+ * @pre Get result count by calling mv_image_classification_get_result_count()
+ */
+int mv_image_classification_get_result(mv_image_classification_h handle, unsigned int index,
+ unsigned long *frame_number, const char **label);
/**
* @brief Set user-given model information.
virtual void perform(mv_source_h &mv_src) = 0;
virtual void performAsync(ImageClassificationInput &input) = 0;
virtual ImageClassificationResult &getOutput() = 0;
+ virtual ImageClassificationResult &getOutputCache() = 0;
};
} // machine_learning
explicit ImageClassification(std::shared_ptr<Config> config);
virtual ~ImageClassification() = default;
- void preDestroy();
- void setEngineInfo(std::string engine_type_name, std::string device_type_name);
- unsigned int getNumberOfEngines();
- const std::string &getEngineType(unsigned int engine_index);
- unsigned int getNumberOfDevices(const std::string &engine_type);
- const std::string &getDeviceType(const std::string &engine_type, unsigned int device_index);
- void configure();
- void prepare();
- void perform(mv_source_h &mv_src);
- void performAsync(ImageClassificationInput &input);
- ImageClassificationResult &getOutput();
+ void preDestroy() override;
+ void setEngineInfo(std::string engine_type_name, std::string device_type_name) override;
+ unsigned int getNumberOfEngines() override;
+ const std::string &getEngineType(unsigned int engine_index) override;
+ unsigned int getNumberOfDevices(const std::string &engine_type) override;
+ const std::string &getDeviceType(const std::string &engine_type, unsigned int device_index) override;
+ void configure() override;
+ void prepare() override;
+ void perform(mv_source_h &mv_src) override;
+ void performAsync(ImageClassificationInput &input) override;
+ ImageClassificationResult &getOutput() override;
+ ImageClassificationResult &getOutputCache() override;
};
} // machine_learning
return _current_result;
}
+template<typename T> ImageClassificationResult &ImageClassification<T>::getOutputCache()
+{
+ return _current_result;
+}
+
template<typename T> void ImageClassification<T>::performAsync(ImageClassificationInput &input)
{
if (!_async_manager) {
OutputBaseType &ImageClassificationAdapter::getOutputCache()
{
- throw InvalidOperation("Not support yet.");
+ return _image_classification->getOutputCache();
}
}
return MEDIA_VISION_ERROR_NONE;
}
-int mv_image_classification_get_label(mv_image_classification_h handle, const char **out_label)
+int mv_image_classification_get_result_count(mv_image_classification_h handle, unsigned int *result_cnt)
{
- MEDIA_VISION_SUPPORT_CHECK(mv_check_feature_key(feature_keys, num_keys, false));
+ MEDIA_VISION_SUPPORT_CHECK(mv_check_feature_key(feature_keys, num_keys, true));
MEDIA_VISION_INSTANCE_CHECK(handle);
- MEDIA_VISION_NULL_ARG_CHECK(out_label);
+ MEDIA_VISION_INSTANCE_CHECK(result_cnt);
MEDIA_VISION_FUNCTION_ENTER();
try {
- const auto &result =
- static_cast<ImageClassificationResult &>(machine_learning_native_get_result(handle, TASK_NAME));
+ auto &result = static_cast<ImageClassificationResult &>(machine_learning_native_get_result(handle, TASK_NAME));
+ // As of now, the result count of image classification task is always 1.
+ // TODO. consider for Multilabel image classification model later.
+ *result_cnt = static_cast<unsigned int>(!result.label.empty());
+ } catch (const BaseException &e) {
+ LOGE("%s", e.what());
+ return e.getError();
+ }
+
+ MEDIA_VISION_FUNCTION_LEAVE();
+
+ return MEDIA_VISION_ERROR_NONE;
+}
+
+int mv_image_classification_get_result(mv_image_classification_h handle, unsigned int index,
+ unsigned long *frame_number, const char **label)
+{
+ MEDIA_VISION_SUPPORT_CHECK(mv_check_feature_key(feature_keys, num_keys, true));
+ MEDIA_VISION_INSTANCE_CHECK(handle);
+ MEDIA_VISION_INSTANCE_CHECK(frame_number);
+ MEDIA_VISION_INSTANCE_CHECK(label);
+
+ MEDIA_VISION_FUNCTION_ENTER();
- *out_label = result.label.c_str();
+ try {
+ auto &result =
+ static_cast<ImageClassificationResult &>(machine_learning_native_get_result_cache(handle, TASK_NAME));
+ // As of now, the result count of image classification task is always 1.
+ unsigned int result_cnt = static_cast<unsigned int>(!result.label.empty());
+ if (index >= result_cnt) {
+ LOGE("Invalid index(index = %u, result count = %u).", index, result_cnt);
+ return MEDIA_VISION_ERROR_INVALID_PARAMETER;
+ }
+
+ *frame_number = result.frame_number;
+ *label = result.label.c_str();
} catch (const BaseException &e) {
LOGE("%s", e.what());
return e.getError();
ret = mv_image_classification_inference(handle, mv_source);
ASSERT_EQ(ret, 0);
- const char *label = NULL;
+ unsigned int cnt;
- ret = mv_image_classification_get_label(handle, &label);
+ ret = mv_image_classification_get_result_count(handle, &cnt);
ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
- cout << label << endl;
+ for (unsigned long idx = 0; idx < cnt; ++idx) {
+ unsigned long frame_number;
+ const char *label = NULL;
+
+ ret = mv_image_classification_get_result(handle, idx, &frame_number, &label);
+ ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
+
+ cout << "frame number = " << frame_number << " label = " << label << endl;
+ }
ret = mv_image_classification_destroy(handle);
ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
void image_classification_callback(void *user_data)
{
mv_image_classification_h handle = static_cast<mv_image_classification_h>(user_data);
- unsigned int frame_number = 0;
+ bool is_loop_exit = false;
- while (frame_number++ < MAX_INFERENCE_ITERATION - 10) {
- const char *label = NULL;
+ while (!is_loop_exit) {
+ unsigned int cnt;
- int ret = mv_image_classification_get_label(handle, &label);
+ int ret = mv_image_classification_get_result_count(handle, &cnt);
if (ret == MEDIA_VISION_ERROR_INVALID_OPERATION)
break;
ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
- cout << "Expected label = BANANA"
- << " Actual label = " << label << endl;
+ for (unsigned long idx = 0; idx < cnt; ++idx) {
+ const char *label = NULL;
+ unsigned long frame_number;
- string label_str(label);
+ ret = mv_image_classification_get_result(handle, idx, &frame_number, &label);
+ ASSERT_EQ(ret, MEDIA_VISION_ERROR_NONE);
+
+ if (frame_number > MAX_INFERENCE_ITERATION - 10)
+ is_loop_exit = true;
+
+ cout << "Expected label = BANANA"
+ << " Actual label = " << label << endl;
- transform(label_str.begin(), label_str.end(), label_str.begin(), ::toupper);
+ string label_str(label);
- ASSERT_EQ(label_str, "BANANA");
+ transform(label_str.begin(), label_str.end(), label_str.begin(), ::toupper);
+
+ ASSERT_EQ(label_str, "BANANA");
+ }
}
}
projects / platform / core / api / mediavision.git / commitdiff