chore: import upstream snapshot with attribution

2026-07-13 13:25:10 +08:00
commit c397331b1e
3684 changed files with 990993 additions and 0 deletions
@@ -0,0 +1,160 @@
+"""
+  Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights
+  Reserved. MIT License  (https://opensource.org/licenses/MIT)
+  
+  2022-2023 by zhaomingwork@qq.com  
+"""
+
+# pip install websocket-client
+import ssl
+from websocket import ABNF
+from websocket import create_connection
+from queue import Queue
+import threading
+import traceback
+import json
+import time
+import numpy as np
+
+
+# class for recognizer in websocket
+class Funasr_websocket_recognizer:
+    """
+    python asr recognizer lib
+
+    """
+
+    def __init__(
+        self,
+        host="127.0.0.1",
+        port="30035",
+        is_ssl=True,
+        chunk_size="0, 10, 5",
+        chunk_interval=10,
+        mode="offline",
+        wav_name="default",
+    ):
+        """
+        host: server host ip
+        port: server port
+        is_ssl: True for wss protocal, False for ws
+        """
+        try:
+            if is_ssl == True:
+                ssl_context = ssl.SSLContext()
+                ssl_context.check_hostname = False
+                ssl_context.verify_mode = ssl.CERT_NONE
+                uri = "wss://{}:{}".format(host, port)
+                ssl_opt = {"cert_reqs": ssl.CERT_NONE}
+            else:
+                uri = "ws://{}:{}".format(host, port)
+                ssl_context = None
+                ssl_opt = None
+            self.host = host
+            self.port = port
+
+            self.msg_queue = Queue()  # used for recognized result text
+
+            print("connect to url", uri)
+            self.websocket = create_connection(uri, ssl=ssl_context, sslopt=ssl_opt)
+
+            self.thread_msg = threading.Thread(
+                target=Funasr_websocket_recognizer.thread_rec_msg, args=(self,)
+            )
+            self.thread_msg.start()
+            chunk_size = [int(x) for x in chunk_size.split(",")]
+            stride = int(60 * chunk_size[1] / chunk_interval / 1000 * 16000 * 2)
+            chunk_num = (len(audio_bytes) - 1) // stride + 1
+
+            message = json.dumps(
+                {
+                    "mode": mode,
+                    "chunk_size": chunk_size,
+                    "encoder_chunk_look_back": 4,
+                    "decoder_chunk_look_back": 1,
+                    "chunk_interval": chunk_interval,
+                    "wav_name": wav_name,
+                    "is_speaking": True,
+                }
+            )
+
+            self.websocket.send(message)
+
+            print("send json", message)
+
+        except Exception as e:
+            print("Exception:", e)
+            traceback.print_exc()
+
+    # threads for rev msg
+    def thread_rec_msg(self):
+        try:
+            while True:
+                msg = self.websocket.recv()
+                if msg is None or len(msg) == 0:
+                    continue
+                msg = json.loads(msg)
+
+                self.msg_queue.put(msg)
+        except Exception as e:
+            print("client closed")
+
+    # feed data to asr engine, wait_time means waiting for result until time out
+    def feed_chunk(self, chunk, wait_time=0.01):
+        try:
+            self.websocket.send(chunk, ABNF.OPCODE_BINARY)
+            # loop to check if there is a message, timeout in 0.01s
+            while True:
+                msg = self.msg_queue.get(timeout=wait_time)
+                if self.msg_queue.empty():
+                    break
+
+            return msg
+        except:
+            return ""
+
+    def close(self, timeout=1):
+        message = json.dumps({"is_speaking": False})
+        self.websocket.send(message)
+        # sleep for timeout seconds to wait for result
+        time.sleep(timeout)
+        msg = ""
+        while not self.msg_queue.empty():
+            msg = self.msg_queue.get()
+
+        self.websocket.close()
+        # only resturn the last msg
+        return msg
+
+
+if __name__ == "__main__":
+
+    print("example for Funasr_websocket_recognizer")
+    import wave
+
+    wav_path = "/Users/zhifu/Downloads/modelscope_models/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav"
+    with wave.open(wav_path, "rb") as wav_file:
+        params = wav_file.getparams()
+        frames = wav_file.readframes(wav_file.getnframes())
+        audio_bytes = bytes(frames)
+
+    stride = int(60 * 10 / 10 / 1000 * 16000 * 2)
+    chunk_num = (len(audio_bytes) - 1) // stride + 1
+    # create an recognizer
+    rcg = Funasr_websocket_recognizer(
+        host="127.0.0.1", port="10095", is_ssl=True, mode="2pass", chunk_size="0,10,5"
+    )
+    # loop to send chunk
+    for i in range(chunk_num):
+
+        beg = i * stride
+        data = audio_bytes[beg : beg + stride]
+
+        text = rcg.feed_chunk(data, wait_time=0.02)
+        if len(text) > 0:
+            print("text", text)
+        time.sleep(0.05)
+
+    # get last message
+    text = rcg.close(timeout=3)
+    print("text", text)