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Update app.py
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app.py
CHANGED
@@ -474,17 +474,18 @@ with demo:
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with gr.Column():
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gr.Markdown('''
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### This space allows you to:
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''')
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with gr.Column():
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gr.Markdown('''
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### 1. Copy any Youtube video URL to box below
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''')
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examples = gr.Examples(examples=
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[ "https://www.youtube.com/watch?v=nlMuHtV82q8&ab_channel=NothingforSale24",
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@@ -509,7 +510,7 @@ with demo:
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gr.Markdown('''
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##### Here you can start the transcription and translation process.
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##### Be aware that processing will last some time. With base model it is around 3x speed
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##### Please select source language for better transcriptions. Using 'Let the model analyze' makes mistakes sometimes and may lead to bad transcriptions
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''')
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selected_source_lang.render()
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selected_whisper_model.render()
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@@ -530,9 +531,9 @@ with demo:
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with gr.Column():
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gr.Markdown('''
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##### PLEASE READ BELOW
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selected_translation_lang_2.render()
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translate_transcriptions_button = gr.Button("Step 3. Translate transcription")
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translate_transcriptions_button.click(translate_transcriptions, [transcription_df, selected_translation_lang_2], [transcription_and_translation_df, subtitle_files])
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with gr.Column():
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gr.Markdown('''
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### This space allows you to:
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1. Download youtube video with a given url
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2. Watch it in the first video component
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3. Run automatic speech recognition on the video using fast Whisper models
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4. Translate the recognized transcriptions to 26 languages supported by deepL
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5. Download generated subtitles in .vtt and .srt formats
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6. Watch the the original video with generated subtitles
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''')
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with gr.Column():
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gr.Markdown('''
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### 1. Copy any Youtube video URL to box below
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(But please **consider using short videos** so others won't get queued) or click one of the examples and then press button "1. Download Youtube video"-button:
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''')
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examples = gr.Examples(examples=
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[ "https://www.youtube.com/watch?v=nlMuHtV82q8&ab_channel=NothingforSale24",
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gr.Markdown('''
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##### Here you can start the transcription and translation process.
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##### Be aware that processing will last some time. With base model it is around 3x speed
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##### **Please select source language** for better transcriptions. Using 'Let the model analyze' makes mistakes sometimes and may lead to bad transcriptions
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''')
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selected_source_lang.render()
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selected_whisper_model.render()
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with gr.Column():
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gr.Markdown('''
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##### PLEASE READ BELOW
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Here you will can translate transcriptions to 26 languages.
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If spoken language is not in the list, translation might not work. In this case original transcriptions are used
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''')
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selected_translation_lang_2.render()
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translate_transcriptions_button = gr.Button("Step 3. Translate transcription")
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translate_transcriptions_button.click(translate_transcriptions, [transcription_df, selected_translation_lang_2], [transcription_and_translation_df, subtitle_files])
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