| 25 | |
| 26 | |
| 27 | int prepare (const char *json_params) |
| 28 | { |
| 29 | std::lock_guard<std::mutex> lock (models_mutex); |
| 30 | |
| 31 | std::shared_ptr<BaseClassifier> model = NULL; |
| 32 | BaseClassifier::ml_logger->trace ("(Prepararing)Incoming json: {}", json_params); |
| 33 | struct BrainFlowModelParams key ( |
| 34 | (int)BrainFlowMetrics::MINDFULNESS, (int)BrainFlowClassifiers::DEFAULT_CLASSIFIER); |
| 35 | int res = string_to_brainflow_model_params (json_params, &key); |
| 36 | if (res != (int)BrainFlowExitCodes::STATUS_OK) |
| 37 | { |
| 38 | return res; |
| 39 | } |
| 40 | if (ml_models.find (key) != ml_models.end ()) |
| 41 | { |
| 42 | return (int)BrainFlowExitCodes::ANOTHER_CLASSIFIER_IS_PREPARED_ERROR; |
| 43 | } |
| 44 | |
| 45 | if ((key.metric == (int)BrainFlowMetrics::USER_DEFINED) && |
| 46 | (key.classifier == (int)BrainFlowClassifiers::DYN_LIB_CLASSIFIER)) |
| 47 | { |
| 48 | model = std::shared_ptr<BaseClassifier> (new DynLibClassifier (key)); |
| 49 | } |
| 50 | else if ((key.metric == (int)BrainFlowMetrics::USER_DEFINED) && |
| 51 | (key.classifier == (int)BrainFlowClassifiers::ONNX_CLASSIFIER)) |
| 52 | { |
| 53 | model = std::shared_ptr<BaseClassifier> (new OnnxClassifier (key)); |
| 54 | } |
| 55 | else if ((key.metric == (int)BrainFlowMetrics::MINDFULNESS) && |
| 56 | (key.classifier == (int)BrainFlowClassifiers::DEFAULT_CLASSIFIER)) |
| 57 | { |
| 58 | model = std::shared_ptr<BaseClassifier> (new MindfulnessClassifier (key)); |
| 59 | } |
| 60 | else if ((key.metric == (int)BrainFlowMetrics::RESTFULNESS) && |
| 61 | (key.classifier == (int)BrainFlowClassifiers::DEFAULT_CLASSIFIER)) |
| 62 | { |
| 63 | model = std::shared_ptr<BaseClassifier> (new RestfulnessClassifier (key)); |
| 64 | } |
| 65 | else |
| 66 | { |
| 67 | return (int)BrainFlowExitCodes::UNSUPPORTED_CLASSIFIER_AND_METRIC_COMBINATION_ERROR; |
| 68 | } |
| 69 | |
| 70 | res = model->prepare (); |
| 71 | if (res != (int)BrainFlowExitCodes::STATUS_OK) |
| 72 | { |
| 73 | BaseClassifier::ml_logger->error ("Unable to prepare model. Please refer to logs above."); |
| 74 | model = NULL; |
| 75 | } |
| 76 | else |
| 77 | { |
| 78 | ml_models[key] = model; |
| 79 | } |
| 80 | return res; |
| 81 | } |
| 82 | |
| 83 | int predict (double *data, int data_len, double *output, int *output_len, const char *json_params) |
| 84 | { |
no test coverage detected