add infer test for sond models

egs_modelscope/speaker_diarization/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/unit_test.py → egs_modelscope/speaker_diarization/speech_diarization_sond-en-us-callhome-8k-n16k4-pytorch/infer.py

@@ -14,13 +14,12 @@ inference_diar_pipline = pipeline(
 )
 
 # 以 audio_list 作为输入，其中第一个音频为待检测语音，后面的音频为不同说话人的声纹注册语音
-audio_list = [[
+audio_list = [
     "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/record.wav",
     "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/spk_A.wav",
     "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/spk_B.wav",
     "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/spk_B1.wav"
-]]
+]
 
 results = inference_diar_pipline(audio_in=audio_list)
-for rst in results:
-    print(rst["value"])
+print(results)

egs_modelscope/speaker_diarization/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/infer.py

@@ -0,0 +1,26 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+
+# 初始化推理 pipeline
+# 当以原始音频作为输入时使用配置文件 sond.yaml，并设置 mode 为sond_demo
+inference_diar_pipline = pipeline(
+    mode="sond_demo",
+    num_workers=0,
+    task=Tasks.speaker_diarization,
+    diar_model_config="sond.yaml",
+    model='damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch',
+    sv_model="damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch",
+    sv_model_revision="master",
+)
+
+# 以 audio_list 作为输入，其中第一个音频为待检测语音，后面的音频为不同说话人的声纹注册语音
+audio_list = [
+    "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/record.wav",
+    "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk1.wav",
+    "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk2.wav",
+    "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk3.wav",
+    "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_data/speaker_diarization/spk4.wav",
+]
+
+results = inference_diar_pipline(audio_in=audio_list)
+print(results)