Added example script for real-time microphone inference

examples/detect_from_microphone.py

@@ -0,0 +1,59 @@
+# Copyright 2022 David Scripka. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Imports
+import os
+import plotext as plt
+import sounddevice
+import numpy as np
+from openwakeword.detect import Model
+
+# Get microphone stream
+mic_stream = sounddevice.InputStream(
+    samplerate=16000,
+    blocksize=1280,
+    device = 3,
+    dtype = np.int16,
+)
+
+# Load openwakeword model(s)
+model_name = "hey_mycroft_v1"
+model = Model(
+    wakeword_model_paths=[os.path.join("../", "openwakeword", "resources", "models", model_name + ".onnx")],
+    input_sizes=[16]
+)
+
+# Run capture loop, checking for hotwords
+if __name__ == "__main__":
+    # Start the mic stream
+    mic_stream.start()
+
+    # Create a prediction buffer
+    prediction_buffer = [0]*30
+    while True:
+        # Get audio
+        audio, overflowed = mic_stream.read(1280)
+        audio = audio.squeeze()
+
+        # Feed to openWakeWord model
+        prediction = model.predict(audio)
+        prediction_buffer = prediction_buffer[1:] + [round(prediction[model_name], 2)]
+        
+        # Plot predictions in graph
+        plt.cld()
+        plt.clt()
+        plt.plot(prediction_buffer)
+        plt.ylim(0,1)
+        plt.show()
+        plt.sleep(0.005)