diff --git a/main.py b/main.py
index fc60fb4..e5bbdf1 100644
--- a/main.py
+++ b/main.py
@@ -5,8 +5,37 @@ from math import ceil
from itertools import product
from rknnlite.api import RKNNLite
import threading
+import sounddevice as sd
+import queue
+import json
+from vosk import Model, KaldiRecognizer
import time
+def speech_loop():
+ global latest_speech
+ model = Model("./vosk-model-small-en-us-0.15")
+ rec = KaldiRecognizer(model, 16000)
+ q = queue.Queue()
+
+ def callback(indata, frames, time, status):
+ if status:
+ print(status)
+ q.put(bytes(indata))
+
+ with sd.RawInputStream(samplerate=16000, blocksize=8000, dtype='int16',
+ channels=1, callback=callback):
+ while True:
+ data = q.get()
+ if rec.AcceptWaveform(data):
+ result = json.loads(rec.Result())
+ latest_speech = result
+ print(".", result)
+ else:
+ partial = json.loads(rec.PartialResult())
+ latest_speech = partial
+ print("...", partial, end='\r')
+
+
# --- RetinaFace Utilities ---
def letterbox_resize(image, size, bg_color):
target_width, target_height = size
@@ -143,14 +172,14 @@ def background_loop():
conf = data[4]
box_center = np.array([(x1 + x2) / 2, (y1 + y2) / 2])
offset = box_center - frame_center
- face_data.append({
- "box": [x1, y1, x2, y2],
- "confidence": float(conf),
- "offset_from_center": {
- "x": float(offset[0]),
- "y": float(offset[1])
- }
- })
+ # face_data.append({
+ # "box": [x1, y1, x2, y2],
+ # "confidence": float(conf),
+ # "offset_from_center": {
+ # "x": float(offset[0]),
+ # "y": float(offset[1])
+ # }
+ # })
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
cv2.putText(frame, f'{conf:.4f}', (x1, y1 + 12), cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 255, 255))
for j in range(5):
@@ -171,7 +200,29 @@ app = Flask(__name__)
@app.route('/')
def index():
- return Response(stream_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
+ return '''
+
+ RetinaFace + Speech
+
+ Live Stream
+ 
+ Live Speech
+
+
+
+
+ '''
+
+
def stream_frames():
while True:
@@ -183,8 +234,14 @@ def stream_frames():
def get_faces():
return jsonify(latest_faces)
+@app.route('/speech')
+def get_speech():
+ return jsonify(latest_speech)
+
+
# --- Start Background Thread ---
threading.Thread(target=background_loop, daemon=True).start()
+threading.Thread(target=speech_loop, daemon=True).start()
if __name__ == '__main__':
app.run(host='0.0.0.0', port=5000)