Update app.py

app.py

@@ -15,13 +15,13 @@ if not os.path.exists(works_path):
   os.makedirs(works_path)
 print('作品目录：' + works_path)
 
-modelname = "small"
-model = whisper.load_model(modelname) #tiny、base、small、medium（可用）、large
+#model_size = "small"
+#model = whisper.load_model(model_size) #tiny、base、small、medium（可用）、large
 
-def transcript(audiofile, prompt, output_dir):
-    os.system(f"whisper {audiofile} --model {modelname} --language zh --initial_prompt {prompt} --output_dir {output_dir}")
+def transcript(model_size, audiofile, prompt, output_dir):
+    os.system(f"whisper {audiofile} --model {model_size} --language zh --initial_prompt {prompt} --output_dir {output_dir}")
 
-def audio_recog(audiofile):
+def audio_recog(model_size, 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")
@@ -32,20 +32,20 @@ def audio_recog(audiofile):
     
     prompt = "以下是普通话的句子"
     filename = os.path.splitext(os.path.basename(audiofile))[0]
-    output_txt = works_path + '/' + filename + '.txt'
-    output_srt = works_path + '/' + filename + '.srt'
+    text_file = works_path + '/' + filename + '.txt'
+    srt_file = works_path + '/' + filename + '.srt'
     
     output_dir = works_path
-    transcript(audiofile, prompt, output_dir)
-    with open(output_txt, "r") as f:
+    transcript(model_size, audiofile, prompt, output_dir)
+    with open(text_file, "r") as f:
         text_output = f.read()
         print("text：" + text_output)
-    print("text文件：" + output_txt)
+    print("text文件：" + text_file)
 
-    with open(output_srt, "r") as f:
+    with open(srt_file, "r") as f:
         srt_output = f.read()
         print("srt：" + srt_output)
-    print("srt文件：" + output_srt)
+    print("srt文件：" + srt_file)
     
     utc_dt = datetime.datetime.utcnow()
     beijing_dt = utc_dt.astimezone(datetime.timezone(datetime.timedelta(hours=16)))
@@ -53,57 +53,31 @@ def audio_recog(audiofile):
     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, srt_output
+    return text_output, text_file, srt_output, srt_file
 
-def video_recog(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")
-    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")
-      
+def video_recog(model_size, filepath):
     filename = os.path.splitext(os.path.basename(filepath))[0]
     worksfile = works_path + '/works_' + filename + '.mp4'
     print("视频文件：" + filepath)
     
-    # 提取音频为aac
+    # 提取音频为mp3
     audiofile = works_path + '/' + filename + '.mp3'
     os.system(f"ffmpeg -i {filepath} -vn -c:a libmp3lame -q:a 4 {audiofile}")
-    print("音频文件：" + audiofile)
     
-    prompt = "以下是普通话的句子"
-    output_txt = works_path + '/' + filename + '.txt'
-    output_srt = works_path + '/' + filename + '.srt'
+    #识别音频文件
+    text_output, text_file, srt_output, srt_file = audio_recog(model_size, audiofile)
     
-    output_dir = works_path
-    transcript(audiofile, prompt, output_dir)
-    with open(output_txt, "r") as f:
-        text_output = f.read()
-        print("text：" + text_output)
-    print("text文件：" + output_txt)
-
-    with open(output_srt, "r") as f:
-        srt_output = f.read()
-        print("srt：" + srt_output)
-    print("srt文件：" + output_srt)
-    
-    # 给视频添加字幕
-    os.system(f"ffmpeg -i {filepath} -i {output_srt} -c:s mov_text -c:v copy -c:a copy {worksfile}")
-    print("作品：" + worksfile)
+#    # 给视频添加字幕
+#    os.system(f"ffmpeg -i {filepath} -i {srt_file} -c:s mov_text -c:v copy -c:a copy {worksfile}")
+#    print("作品：" + worksfile)
     
-    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, srt_output, worksfile
+    return text_output, text_file, srt_output, srt_file
 
 css_style = "#fixed_size_img {height: 240px;} " \
             "#overview {margin: auto;max-width: 400px; max-height: 400px;}"
 
 title = "音视频转录 by宁侠"
-description = ""
+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和字幕。这样，您就可以轻松地记录下重要的语音内容，或者为视频添加精准的字幕。现在就���试试我们的音视频转录服务吧，让您的生活和工作更加便捷！"
 
 examples_path = 'examples/'
 examples = [[examples_path + 'demo_shejipuhui.mp4']]
@@ -128,41 +102,46 @@ with gr.Blocks(title=title, css=css_style) as demo:
                     </h1>
       ''')
     gr.Markdown(description)
-    video_state = gr.State()
-    audio_state = gr.State()
+    
+    with gr.Tab("🔊音频转录 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_model_size = gr.components.Radio(label="模型尺寸", choices=["tiny", "base", "small", "medium", "large"], value="small")
+                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_srt_output = gr.Textbox(label="📖SRT字幕内容 SRT Subtitles", max_lines=10)
+                audio_srt_file = gr.File(label="📖SRT字幕文件 SRT 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_model_size, audio_input], outputs=[audio_text_output, audio_text_file, audio_srt_output, audio_srt_file])
+#    audio_subtitles_button.click(audio_subtitles, inputs=[audio_text_input], outputs=[audio_output])
+
     with gr.Tab("🎥视频转录 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_model_size = gr.components.Radio(label="模型尺寸", choices=["tiny", "base", "small", "medium", "large"], value="small")
                 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")
-                video_srt_output = gr.Textbox(label="📖SRT字幕内容 SRT Subtitles")
+                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")
+                video_srt_output = gr.Textbox(label="📖SRT字幕内容 SRT Subtitles", max_lines=10)
+                video_srt_file = gr.File(label="📖SRT字幕文件 SRT 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_srt_output, video_output])
+    video_recog_button.click(video_recog, inputs=[video_model_size, video_input], outputs=[video_text_output, video_text_file, video_srt_output, video_srt_file])
 #    video_subtitles_button.click(video_subtitles, inputs=[video_text_input], outputs=[video_output])
 
-    with gr.Tab("🔊音频转录 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")
-                audio_srt_output = gr.Textbox(label="📖SRT字幕内容 SRT Subtitles")
-                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_srt_output])
-#    audio_subtitles_button.click(audio_subtitles, inputs=[audio_text_input], outputs=[audio_output])
-
 # start gradio service in local
-demo.queue(api_open=False).launch(debug=True)
+demo.queue(api_open=False).launch(debug=True)