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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+examples/demo_shejipuhui.mp4 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,137 @@
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+import gradio as gr
+import datetime
+import os
+
+#获取当前北京时间
+utc_dt = datetime.datetime.utcnow()
+beijing_dt = utc_dt.astimezone(datetime.timezone(datetime.timedelta(hours=16)))
+formatted = beijing_dt.strftime("%Y-%m-%d_%H")
+print(f"北京时间: {beijing_dt.year}年{beijing_dt.month}月{beijing_dt.day}日 "
+      f"{beijing_dt.hour}时{beijing_dt.minute}分{beijing_dt.second}秒")
+#创建作品存放目录
+works_path = '../works_audio_video_transcribe/' + formatted
+if not os.path.exists(works_path):
+  os.makedirs(works_path)
+print('作品目录：' + works_path)
+
+inference_pipeline = pipeline(
+    task=Tasks.auto_speech_recognition,
+    model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
+    
+def transcript(audiofile, text_file):
+    rec_result = inference_pipeline(audio_in=audiofile)
+    print(rec_result['text'])
+    
+    with open(text_file, "w") as f:
+        f.write(rec_result['text'])
+        
+    return rec_result['text']
+
+def audio_recog(audiofile):
+    utc_dt = datetime.datetime.utcnow()
+    beijing_dt = utc_dt.astimezone(datetime.timezone(datetime.timedelta(hours=16)))
+    formatted = beijing_dt.strftime("%Y-%m-%d_%H-%M-%S")
+    print(f"开始时间: {beijing_dt.year}年{beijing_dt.month}月{beijing_dt.day}日 "
+      f"{beijing_dt.hour}时{beijing_dt.minute}分{beijing_dt.second}秒")
+      
+    print("音频文件：" + audiofile)
+    
+    filename = os.path.splitext(os.path.basename(audiofile))[0]
+    text_file = works_path + '/' + filename + '.txt'
+    
+    text_output = transcript(audiofile, text_file)
+    
+    utc_dt = datetime.datetime.utcnow()
+    beijing_dt = utc_dt.astimezone(datetime.timezone(datetime.timedelta(hours=16)))
+    formatted = beijing_dt.strftime("%Y-%m-%d_%H-%M-%S")
+    print(f"结束时间: {beijing_dt.year}年{beijing_dt.month}月{beijing_dt.day}日 "
+      f"{beijing_dt.hour}时{beijing_dt.minute}分{beijing_dt.second}秒")
+    
+    return text_output, text_file
+
+def video_recog(filepath):
+    filename = os.path.splitext(os.path.basename(filepath))[0]
+    worksfile = works_path + '/works_' + filename + '.mp4'
+    print("视频文件：" + filepath)
+    
+    utc_dt = datetime.datetime.utcnow()
+    beijing_dt = utc_dt.astimezone(datetime.timezone(datetime.timedelta(hours=16)))
+    formatted = beijing_dt.strftime("%Y-%m-%d_%H-%M-%S.%f")
+    
+    # 提取音频为mp3
+    audiofile = works_path + '/' + formatted + '.mp3'
+    os.system(f"ffmpeg -i {filepath} -vn -c:a libmp3lame -q:a 4 {audiofile}")
+    
+    #识别音频文件
+    text_output, text_file = audio_recog(audiofile)
+    
+    return text_output, text_file
+
+css_style = "#fixed_size_img {height: 240px;} " \
+            "#overview {margin: auto;max-width: 400px; max-height: 400px;}"
+
+title = "音视频识别 by宁侠"
+description = "您只需要上传一段音频或视频文件，我们的服务会快速对其进行语音识别，然后生成相应的文字。这样，您就可以轻松地记录下重要的语音内容。现在就来试试我们的音视频识别服务吧，让您的生活和工作更加便捷！"
+
+examples_path = 'examples/'
+examples = [[examples_path + 'demo_shejipuhui.mp4']]
+
+# gradio interface
+with gr.Blocks(title=title, css=css_style) as demo:
+    gr.HTML('''
+      <div style="text-align: center; max-width: 720px; margin: 0 auto;">
+                  <div
+                    style="
+                      display: inline-flex;
+                      align-items: center;
+                      gap: 0.8rem;
+                      font-size: 1.75rem;
+                    "
+                  >
+                    <h1 style="font-family:  PingFangSC; font-weight: 500; font-size: 36px; margin-bottom: 7px;">
+                      音视频识别
+                    </h1>
+                    <h1 style="font-family: PingFangSC; font-weight: 500; line-height: 1.5em; font-size: 16px; margin-bottom: 7px;">
+                      by宁侠
+                    </h1>
+      ''')
+    gr.Markdown(description)
+    
+    with gr.Tab("🔊音频识别 Audio Transcribe"):
+        with gr.Row():
+            with gr.Column():
+                audio_input = gr.Audio(label="🔊音频输入 Audio Input", type="filepath")
+                gr.Examples(['examples/paddlespeech.asr-zh.wav', 'examples/demo_shejipuhui.mp3'], [audio_input])
+                audio_recog_button = gr.Button("👂音频识别 Recognize")
+            with gr.Column():
+                audio_text_output = gr.Textbox(label="✏️识别结果 Recognition Result", max_lines=5)
+                audio_text_file = gr.File(label="✏️识别结果文件 Recognition Result File")
+                audio_subtitles_button = gr.Button("添加字幕\nGenerate Subtitles", visible=False)
+                audio_output = gr.Audio(label="🔊音频 Audio", visible=False)
+    
+    audio_recog_button.click(audio_recog, inputs=[audio_input], outputs=[audio_text_output, audio_text_file])
+#    audio_subtitles_button.click(audio_subtitles, inputs=[audio_text_input], outputs=[audio_output])
+
+    with gr.Tab("🎥视频识别 Video Transcribe"):
+        with gr.Row():
+            with gr.Column():
+                video_input = gr.Video(label="🎥视频输入 Video Input")
+                gr.Examples(['examples/demo_shejipuhui.mp4'], [video_input], label='语音识别示例 ASR Demo')
+                video_recog_button = gr.Button("👂视频识别 Recognize")
+                video_output = gr.Video(label="🎥视频 Video", visible=False)
+            with gr.Column():
+                video_text_output = gr.Textbox(label="✏️识别结果 Recognition Result", max_lines=5)
+                video_text_file = gr.File(label="✏️识别结果文件 Recognition Result File")
+                with gr.Row(visible=False):
+                    font_size = gr.Slider(minimum=10, maximum=100, value=32, step=2, label="🔠字幕字体大小 Subtitle Font Size")
+                    font_color = gr.Radio(["black", "white", "green", "red"], label="🌈字幕颜色 Subtitle Color", value='white')
+                video_subtitles_button = gr.Button("添加字幕\nGenerate Subtitles", visible=False)
+                
+    
+    video_recog_button.click(video_recog, inputs=[video_input], outputs=[video_text_output, video_text_file])
+#    video_subtitles_button.click(video_subtitles, inputs=[video_text_input], outputs=[video_output])
+
+# start gradio service in local
+demo.queue(api_open=False).launch(debug=True)

examples/demo_shejipuhui.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8fa2612b7a25e94f8ec3fe96ac88fb01874b8bbed5b7bc10d07ef0555340bc6
+size 4784476

requirements.txt

@@ -0,0 +1,2 @@
+funasr
+torchaudio