diff --git a/EMG_Arm/src/core/model_weights.h b/EMG_Arm/src/core/model_weights.h index 1dd5c94..94a35e2 100644 --- a/EMG_Arm/src/core/model_weights.h +++ b/EMG_Arm/src/core/model_weights.h @@ -1,8 +1,7 @@ /** * @file model_weights.h - * @brief Placeholder for trained model weights. - * - * This file should be generated by the Python script (Training Page -> Export for ESP32). + * @brief Trained LDA model weights exported from Python. + * @date 2026-01-27 21:35:17 */ #ifndef MODEL_WEIGHTS_H @@ -16,11 +15,11 @@ /* Class Names */ static const char* MODEL_CLASS_NAMES[MODEL_NUM_CLASSES] = { - "REST", - "OPEN", - "FIST", - "HOOK_EM", - "THUMBS_UP", + "fist", + "hook_em", + "open", + "rest", + "thumbs_up", }; /* Feature Extractor Parameters */ @@ -29,16 +28,36 @@ static const char* MODEL_CLASS_NAMES[MODEL_NUM_CLASSES] = { /* LDA Intercepts/Biases */ static const float LDA_INTERCEPTS[MODEL_NUM_CLASSES] = { - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f + -14.097581f, -2.018629f, -4.478267f, 1.460458f, -5.562349f }; /* LDA Coefficients (Weights) */ static const float LDA_WEIGHTS[MODEL_NUM_CLASSES][MODEL_NUM_FEATURES] = { - {0.0f}, - {0.0f}, - {0.0f}, - {0.0f}, - {0.0f} + /* fist */ + { + 0.070110f, -0.002554f, 0.043924f, 0.020555f, -0.660305f, 0.010691f, -0.074429f, -0.037253f, + 0.057908f, -0.002655f, 0.042119f, -0.052956f, 0.063822f, 0.006184f, -0.025462f, 0.040815f, + }, + /* hook_em */ + { + -0.002511f, 0.001034f, 0.027889f, 0.026006f, 0.183681f, -0.000773f, 0.016791f, -0.027926f, + -0.023321f, 0.000770f, 0.059023f, -0.056021f, 0.237063f, -0.007423f, 0.082101f, -0.021472f, + }, + /* open */ + { + -0.006170f, 0.000208f, -0.041151f, 0.013271f, 0.054508f, -0.002356f, 0.000170f, 0.012941f, + -0.106180f, 0.003538f, -0.013656f, -0.017712f, 0.131131f, -0.002623f, -0.007022f, 0.024497f, + }, + /* rest */ + { + -0.011094f, 0.000160f, -0.012547f, -0.011058f, 0.130577f, -0.001942f, 0.020823f, -0.001961f, + 0.018021f, -0.000404f, -0.065598f, 0.039676f, 0.018679f, -0.001522f, 0.023302f, -0.008474f, + }, + /* thumbs_up */ + { + -0.016738f, 0.000488f, 0.024199f, -0.024643f, -0.044912f, 0.000153f, -0.011080f, 0.043487f, + 0.051828f, -0.001670f, 0.109633f, 0.004154f, -0.460694f, 0.008616f, -0.104097f, -0.020886f, + }, }; -#endif /* MODEL_WEIGHTS_H */ +#endif /* MODEL_WEIGHTS_H */ \ No newline at end of file diff --git a/emg_gui.py b/emg_gui.py index 59bc103..4849611 100644 --- a/emg_gui.py +++ b/emg_gui.py @@ -1918,14 +1918,17 @@ class PredictionPage(BasePage): print("[DEBUG] Starting Edge Prediction (On-Device)...") try: - # Send "start_predict" command to ESP32 - if hasattr(self.stream, 'ser'): - self.stream.ser.write(b'{"cmd": "start_predict"}\n') - self.stream.running = True + # Use the new interface method to start prediction + if hasattr(self.stream, 'start_predict'): + self.stream.start_predict() + self.stream.running = True else: - # Fallback - self.stream.ser.write(b'{"cmd": "start_predict"}\n') - self.stream.running = True + # Fallback for simulated stream or older interface + # Simulated stream doesn't need 'start_predict', just 'start' + if not self.using_real_hardware: + self.stream.start() + else: + raise RuntimeError("Stream object missing start_predict method") except Exception as e: messagebox.showerror("Start Error", f"Failed to start: {e}") diff --git a/models/emg_lda_classifier.joblib b/models/emg_lda_classifier.joblib index 5f2f6fc..6757e9a 100644 Binary files a/models/emg_lda_classifier.joblib and b/models/emg_lda_classifier.joblib differ diff --git a/serial_stream.py b/serial_stream.py index d3b32a7..cfbd164 100644 --- a/serial_stream.py +++ b/serial_stream.py @@ -240,8 +240,29 @@ class RealSerialStream: start_cmd = {"cmd": "start"} self._send_json(start_cmd) self.state = ConnectionState.STREAMING + self.state = ConnectionState.STREAMING print(f"[SERIAL] Started streaming") + def start_predict(self) -> None: + """ + @brief Start on-device prediction (Edge Inference). + + Sends 'start_predict' command. Device enters PREDICTING state. + Stream receives JSON telemetry instead of raw CSV. + """ + if self.state != ConnectionState.CONNECTED: + raise RuntimeError( + f"Cannot start prediction from state {self.state.name}. " + "Must call connect() first." + ) + + self.serial.reset_input_buffer() + + cmd = {"cmd": "start_predict"} + self._send_json(cmd) + self.state = ConnectionState.STREAMING # Treat as streaming for readline purposes + print(f"[SERIAL] Started prediction mode") + def stop(self) -> None: """ @brief Stop streaming EMG data.