Update app.py

app.py

@@ -1,18 +1,94 @@
 from transformers import pipeline
 import gradio as gr
+import os
+import subprocess
+from pytube import YouTube
+ 
+pipe = pipeline(model="tilos/whisper-small-zh-HK")  # change to "your-username/the-name-you-picked"
 
-pipe = pipeline(model="Chenzhou/Whisper-zh-HK")  # change to "your-username/the-name-you-picked"
+def video2mp3(video_file, output_ext="mp3"):
+    filename, ext = os.path.splitext(video_file)
+    subprocess.call(["ffmpeg", "-y", "-i", video_file, f"{filename}.{output_ext}"],
+                    stdout=subprocess.DEVNULL,
+                    stderr=subprocess.STDOUT)
+    return f"{filename}.{output_ext}"
 
 def transcribe(audio):
     text = pipe(audio)["text"]
     return text
 
-iface = gr.Interface(
-    fn=transcribe, 
-    inputs=gr.Audio(source="microphone", type="filepath"), 
-    outputs="text",
-    title="Whisper Small Cantonese",
-    description="Realtime demo for Cantonese speech recognition using a fine-tuned Whisper small model.",
-)
 
-iface.launch()
+def get_text(url):
+    result = pipe(get_audio(url))
+    return result['text'].strip()
+
+def get_audio(url):
+    website = YouTube(url)
+    video = website.streams.filter(only_audio=True).first()
+    out_file = video.download(output_path=".")
+    base, ext = os.path.splitext(out_file)
+    new_file = base + '.mp3'
+    os.rename(out_file, new_file)
+    audio = new_file
+    return audio
+
+def offline_video(video):
+    audio_file = video2mp3(video)
+    text = transcribe(audio_file)
+    return text
+
+
+with gr.Blocks() as demo:
+
+    # video file input
+    gr.Interface(
+            title="Whisper: Real Time Cantonese Recognition",
+            description="Realtime demo for Cantonese speech recognition using a fine-tuned Whisper small model. "
+                        "Generate zh-HK subtitle from video file, audio file, your microphone, and Youtube URL",
+            fn=offline_video,
+            inputs="video",
+            outputs="text",
+            allow_flagging="never",
+        )
+
+    # audio file input
+    with gr.Row():
+        with gr.Column():
+            input_audio = gr.Audio(source="upload", type="filepath")
+            micro_btn = gr.Button('Generate Voice Subtitles')
+        with gr.Column():
+            output_audio = gr.Textbox(placeholder='Transcript from audio', label='Subtitles')
+            micro_btn.click(transcribe, inputs=input_audio, outputs=output_audio)
+    """
+    gr.Interface(
+            fn=transcribe,
+            title="Whisper: zh-HK Subtitle Generator",
+            description="Generate zh-HK subtitle from audio file, your microphone and Youtube",
+            inputs = gr.Audio(source="upload", type="filepath", optional=True),
+            outputs = "text",
+            allow_flagging= "never",
+    )
+    """
+
+    # microphone input
+    with gr.Row():
+        with gr.Column():
+            input_mircro = gr.Audio(source="microphone", type="filepath")
+            micro_btn = gr.Button('Generate Voice Subtitles')
+        with gr.Column():
+            output_micro = gr.Textbox(placeholder='Transcript from mic', label='Subtitles')
+            micro_btn.click(transcribe, inputs=input_mircro, outputs=output_micro)
+
+    # Youtube url input
+    with gr.Row():
+        with gr.Column():
+            inputs_url = gr.Textbox(placeholder='Youtube URL', label='URL')
+            url_btn = gr.Button('Generate Youtube Video Subtitles')
+            examples = gr.Examples(examples=["https://www.youtube.com/watch?v=Yw4EoGWe0vw"],inputs=[inputs_url])
+        with gr.Column():
+            output_url = gr.Textbox(placeholder='Transcript from video.', label='Transcript')
+            url_btn.click(get_text, inputs=inputs_url, outputs=output_url )
+
+
+
+demo.launch(debug=True)