modify buffer size

asr/sherpa_ncnn_asr.py

@@ -27,6 +27,7 @@ class SherpaNcnnAsr(AsrBase):
         super().__init__()
         self._recognizer = self._create_recognizer()
         logger.info('SherpaNcnnAsr init')
+        print('SherpaNcnnAsr init')
 
     def __del__(self):
         self.__del__()
@@ -60,17 +61,10 @@ class SherpaNcnnAsr(AsrBase):
         time.sleep(3)
         last_result = ""
         logger.info(f'_recognize_loop')
-        while self._stop_event.is_set():
+        print(f'_recognize_loop')
-            logger.info(f'_recognize_loop000')
+
-            self._notify_complete('介绍中国5000年历史文学')
-            logger.info(f'_recognize_loop111')
-            segment_id += 1
-            time.sleep(60)
-            logger.info(f'_recognize_loop222')
-        logger.info(f'_recognize_loop exit')
-'''
         with sd.InputStream(channels=1, dtype="float32", samplerate=self._sample_rate) as s:
-            while not self._stop_event.is_set():
+            while self._stop_event.is_set():
                 samples, _ = s.read(self._samples_per_read)  # a blocking read
                 samples = samples.reshape(-1)
                 self._recognizer.accept_waveform(self._sample_rate, samples)
@@ -89,4 +83,13 @@ class SherpaNcnnAsr(AsrBase):
                         self._notify_complete(result)
                         segment_id += 1
                     self._recognizer.reset()
+'''
+        while self._stop_event.is_set():
+            logger.info(f'_recognize_loop000')
+            self._notify_complete('介绍中国5000年历史文学')
+            logger.info(f'_recognize_loop111')
+            segment_id += 1
+            time.sleep(60)
+            logger.info(f'_recognize_loop222')
+        logger.info(f'_recognize_loop exit')
 '''

human/audio_inference_handler.py

@@ -75,7 +75,7 @@ class AudioInferenceHandler(AudioHandler):
                 batch_size = self._context.batch_size
                 try:
                     mel_batch = self._mal_queue.get(timeout=0.02)
-                    print('AudioInferenceHandler mel_batch:', len(mel_batch), 'size:', self._mal_queue.size())
+                    # print('AudioInferenceHandler mel_batch:', len(mel_batch), 'size:', self._mal_queue.size())
                 except queue.Empty:
                     continue
 
@@ -100,7 +100,6 @@ class AudioInferenceHandler(AudioHandler):
                         self.on_next_handle((None, mirror_index(length, index), audio_frames[i * 2:i * 2 + 2]),
                                             0)
                         index = index + 1
-                    print('AudioInferenceHandler all silence')
                 else:
                     logger.info('infer=======')
                     t = time.perf_counter()

human/audio_mal_handler.py

@@ -20,15 +20,16 @@ class AudioMalHandler(AudioHandler):
 
         EventBus().register('stop', self._on_stop)
 
-        self._queue = SyncQueue(context.batch_size, "AudioMalHandler_queue")
+        self._is_running = True
-        self._exit_event = Event()
+        self._queue = SyncQueue(context.batch_size * 2, "AudioMalHandler_queue")
-        self._thread = Thread(target=self._on_run, name="AudioMalHandlerThread")
-        self._exit_event.set()
-        self._thread.start()
 
         self.frames = []
         self.chunk = context.sample_rate // context.fps
-        self._is_running = True
+
+        self._exit_event = Event()
+        self._exit_event.set()
+        self._thread = Thread(target=self._on_run, name="AudioMalHandlerThread")
+        self._thread.start()
         logger.info("AudioMalHandler init")
 
     def __del__(self):

human/human_render.py

@@ -42,8 +42,14 @@ class HumanRender(AudioHandler):
     def _on_run(self):
         logging.info('human render run')
         while self._exit_event.is_set() and self._is_running:
+            # t = time.time()
             self._run_step()
-            time.sleep(0.038)
+            # delay = time.time() - t
+            delay = 0.03805 # - delay
+            # print(delay)
+            # if delay <= 0.0:
+            #     continue
+            time.sleep(delay)
 
         logging.info('human render exit')
 
@@ -53,7 +59,7 @@ class HumanRender(AudioHandler):
             if value is None:
                 return
             res_frame, idx, audio_frames = value
-            print('voice render queue size', self._queue.size())
+            # print('render queue size', self._queue.size())
             if not self._empty_log:
                 self._empty_log = True
                 logging.info('render render:')

nlp/nlp_base.py

@@ -55,7 +55,7 @@ class NLPBase(AsrObserver):
     def ask(self, question):
         logger.info(f'ask:{question}')
         self._is_running = True
-        task = self._ask_queue.add_task(self._request, question)
+        self._ask_queue.add_task(self._request, question)
         logger.info(f'ask:{question} completed')
 
     def stop(self):

render/video_render.py

@@ -15,28 +15,9 @@ class VideoRender(BaseRender):
     def __init__(self, play_clock, context, human_render):
         super().__init__(play_clock, context, 'Video')
         self._human_render = human_render
-        self._diff_avg_count = 0
 
     def render(self, frame, ps):
         res_frame, idx, type_ = frame
-        clock_time = self._play_clock.clock_time()
-        time_difference = clock_time - ps
-        if abs(time_difference) > self._play_clock.audio_diff_threshold:
-            if self._diff_avg_count < 5:
-                self._diff_avg_count += 1
-            else:
-                if time_difference < -self._play_clock.audio_diff_threshold:
-                    sleep_time = abs(time_difference)
-                    print("Video frame waiting to catch up with audio", sleep_time)
-                    if sleep_time <= 1.0:
-                        time.sleep(sleep_time)
-
-                # elif time_difference > self._play_clock.audio_diff_threshold:  # 视频比音频快超过10ms
-                #     print("Video frame dropped to catch up with audio")
-                #     continue
-
-        else:
-            self._diff_avg_count = 0
 
         if type_ == 0:
             combine_frame = self._context.frame_list_cycle[idx]

test/test_mzzsfy_tts.py

@@ -44,7 +44,8 @@ def main():
     from io import BytesIO
 
     async def fetch_audio():
-        url = "http://localhost:8082/v1/audio/speech"
+        # url = "http://localhost:8082/v1/audio/speech"
+        url = "https://tts.mzzsfy.eu.org/v1/audio/speech"
         data = {
             "model": "tts-1",
             "input": "写了一个高性能tts(文本转声音)工具,5千字仅需5秒,免费使用",

tts/tts_base.py

@@ -32,13 +32,13 @@ class TTSBase(NLPCallback):
         self._handle = value
 
     async def _request(self, txt: str, index):
-        print('_request:', txt)
+        # print('_request:', txt)
         t = time.time()
         stream = await self._on_request(txt)
         if stream is None:
-            print(f'-------stream is None')
+            logger.warn(f'-------stream is None')
             return
-        print(f'-------tts time:{time.time() - t:.4f}s')
+        logger.info(f'-------tts time:{time.time() - t:.4f}s, txt:{txt}')
         if self._handle is not None and self._is_running:
             await self._on_handle(stream, index)
         else:
@@ -59,13 +59,13 @@ class TTSBase(NLPCallback):
     def message(self, txt):
         txt = txt.strip()
         if len(txt) == 0:
-            logger.info(f'message is empty')
+            # logger.info(f'message is empty')
             return
         logger.info(f'message:{txt}')
         index = 0
         if self._handle is not None:
             index = self._handle.get_index()
-            print(f'message txt-index:{txt}, index {index}')
+            # print(f'message txt-index:{txt}, index {index}')
         self._message_queue.add_task(self._request, txt, index)
 
     def stop(self):

tts/tts_edge_http.py

@@ -22,7 +22,7 @@ class TTSEdgeHttp(TTSBase):
         logger.info(f"TTSEdge init, {voice}")
 
     async def _on_request(self, txt: str):
-        print('TTSEdgeHttp, _on_request, txt:', txt)
+        logger.info(f'TTSEdgeHttp, _on_request, txt:{txt}')
         data = {
             "model": "tts-1",
             "input": txt,
@@ -38,7 +38,7 @@ class TTSEdgeHttp(TTSBase):
                     return stream
                 else:
                     byte_stream = None
-                    return byte_stream
+                    return byte_stream, None
 
     async def _on_handle(self, stream, index):
         print('-------tts _on_handle')

ui/pygame_ui.py

@@ -55,7 +55,11 @@ class PyGameUI:
         if self._queue.empty():
             return
         image = self._queue.get()
-        self._human_image = pygame.image.frombuffer(image.tobytes(), image.shape[1::-1], "RGB")
+        color_format = "RGB"
+        if 4 == image.shape[2]:
+            color_format = "RGBA"
+
+        self._human_image = pygame.image.frombuffer(image.tobytes(), image.shape[1::-1], color_format)
 
     def stop(self):
         logger.info('stop')

utils/async_task_queue.py

@@ -45,7 +45,7 @@ class AsyncTaskQueue:
 
                 await func(*args)  # Execute async function
             except Exception as e:
-                logging.error(f'{self._name} error:', e)
+                logging.error(f'{self._name} error: {e}')
             finally:
                 self._queue.task_done()
 

utils/utils.py

@@ -194,7 +194,7 @@ def config_logging(file_name: str, console_level: int = logging.INFO, file_level
 
     console_handler = logging.StreamHandler()
     console_handler.setFormatter(logging.Formatter(
-        '[%(asctime)s %(levelname)s] %(message)s',
+        '[%(asctime)s.%(msecs)03d %(levelname)s] %(message)s',
         datefmt="%Y/%m/%d %H:%M:%S"
         ))
     console_handler.setLevel(console_level)