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@ -204,7 +204,7 @@ class ROSInterface: |
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# Publisher for Audio Data |
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self.audio_data_pub = rospy.Publisher("/wav_data", numpy_msg(VZ_AudioData), queue_size=10) |
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# For Utku's code: float of cough probabilty from sample |
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self.cough_prob = 90 |
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self.cough_prob = 90.000 |
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self.model_path = '/home/hello-robot/vz_modules/NEU_VZ_ASA/MehrshadTesting/codes/A_CoughDetection/models/' |
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self.cough_classifier_file = self.model_path + 'cough_classifier' |
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@ -213,8 +213,8 @@ class ROSInterface: |
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self.loaded_scaler = pickle.load(open(self.cough_classifier_scaler, 'rb')) |
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# for testing audio collection |
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# self.file_name = 'testing_audio_node1.wav' |
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# self.dir = os.path.join('/home/hello-robot/clone/Robot_Autonomous_Navigation/catkin_ws/src/stretch_ros/vz_acoustic_scene_analysis/scripts/', self.file_name) |
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self.file_name = 'testing_audio_node6.wav' |
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self.dir = os.path.join('/home/hello-robot/clone/Robot_Autonomous_Navigation/catkin_ws/src/stretch_ros/vz_acoustic_scene_analysis/scripts/',
self.file_name) |
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@ -288,7 +288,7 @@ class ROSInterface: |
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flatter_list_np = np.asarray(flatter_list) |
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# Test that the data is good |
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# scipy.io.wavfile.write(self.dir, 16000, flatter_list_np) |
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scipy.io.wavfile.write(self.dir, 16000, flatter_list_np) |
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# remove first 0.2 seconds from wav data |
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self.wav_list.pop(0) |
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@ -296,7 +296,7 @@ class ROSInterface: |
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# Call of Utku's function |
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self.cough_prob = dsp.classify_cough(flatter_list_np,RESPEAKER_RATE,self.loaded_model,self.loaded_scaler) |
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print("%d %% probability of cough" %(self.cough_prob)) |
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print("%d %% probability of cough" %round(self.cough_prob*100,2)) |
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# do something with probability (publish?) |
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except usb.core.USBError: |
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print('Respeaker not on USB bus') |
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