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Update app.py
Browse files
app.py
CHANGED
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@@ -1,5 +1,7 @@
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import os
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import tempfile
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from pathlib import Path
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import gradio as gr
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import ffmpeg
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@@ -16,6 +18,7 @@ def _format_timestamp(seconds: float) -> str:
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millis = ms_rem % 1000
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return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"
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def segments_to_srt(segments: list) -> str:
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lines = []
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for i, seg in enumerate(segments, start=1):
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@@ -28,8 +31,9 @@ def segments_to_srt(segments: list) -> str:
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lines.append(block)
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return "\n".join(lines)
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# -------- Config --------
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MODEL_NAME = "Systran/faster-whisper-small" #
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DEVICE = "cpu"
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OUTPUT_DIR = Path("outputs/subtitles")
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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@@ -38,6 +42,7 @@ print(f"Loading model {MODEL_NAME} on {DEVICE} ...")
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model = WhisperModel(MODEL_NAME, device=DEVICE)
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print("Model loaded.")
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# -------- Core functions --------
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def extract_audio(input_path: str, out_path: str):
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"""Extracts mono 16 kHz WAV using ffmpeg"""
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@@ -54,35 +59,36 @@ def extract_audio(input_path: str, out_path: str):
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msg = stderr.decode() if stderr else str(e)
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raise RuntimeError(f"ffmpeg error: {msg}")
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def transcribe_file_to_srt(file_obj, language: str = "en"):
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"""Transcribe uploaded file to SRT; compatible with HF Spaces"""
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tmp_dir = Path(tempfile.mkdtemp(prefix="subgen_"))
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input_path = Path(file_obj.name)
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if not input_path.exists():
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input_path = tmp_dir / Path(file_obj.name).name
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dst.write(src.read())
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# Extract audio and transcribe
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audio_path = tmp_dir / "audio.wav"
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extract_audio(str(input_path), str(audio_path))
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segments, _ = model.transcribe(str(audio_path), language=language)
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segs = [{"start": s.start, "end": s.end, "text": s.text} for s in segments]
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srt_text = segments_to_srt(segs)
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output_path = OUTPUT_DIR / f"{Path(file_obj.name).stem}.srt"
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with open(output_path, "w", encoding="utf-8") as f:
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f.write(srt_text)
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return str(output_path), "β
Subtitles generated successfully!"
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# -------- Gradio UI --------
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with gr.Blocks(title="AI Subtitle Generator") as demo:
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theme_state = gr.State("light")
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@@ -97,37 +103,38 @@ with gr.Blocks(title="AI Subtitle Generator") as demo:
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else:
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bg = "linear-gradient(135deg, #fdfbfb, #ebedee)"
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color = "#000000"
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return gr.update(
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gr.HTML("<h1 style='text-align:center;'>π¬ AI Subtitle Generator</h1>")
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gr.HTML(
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style_box = gr.HTML("")
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theme_btn = gr.Button("π Toggle Light/Dark Mode")
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with gr.Row():
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input_file = gr.File(label="Upload video/audio file")
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output_file = gr.File(label="Download .srt file")
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def on_click(file):
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srt_path, msg = transcribe_file_to_srt(file)
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return srt_path, msg
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theme_btn.click(toggle_theme, inputs=[theme_state], outputs=[theme_state]).then(
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apply_theme, inputs=[theme_state], outputs=[style_box]
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)
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with gr.Row():
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generate_btn = gr.Button("Generate Subtitles")
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clear_btn = gr.Button("π§Ή Clear")
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generate_btn.click(on_click, inputs=[input_file], outputs=[output_file, status_box])
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clear_btn.click(fn=clear_fields, outputs=[input_file, output_file, status_box])
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gr.HTML(
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if __name__ == "__main__":
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demo.launch()
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# app.py
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import os
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import tempfile
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import uuid
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from pathlib import Path
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import gradio as gr
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import ffmpeg
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millis = ms_rem % 1000
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return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"
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def segments_to_srt(segments: list) -> str:
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lines = []
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for i, seg in enumerate(segments, start=1):
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lines.append(block)
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return "\n".join(lines)
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# -------- Config --------
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MODEL_NAME = "Systran/faster-whisper-small" # good for HF CPU
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DEVICE = "cpu"
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OUTPUT_DIR = Path("outputs/subtitles")
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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model = WhisperModel(MODEL_NAME, device=DEVICE)
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print("Model loaded.")
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# -------- Core functions --------
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def extract_audio(input_path: str, out_path: str):
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"""Extracts mono 16 kHz WAV using ffmpeg"""
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msg = stderr.decode() if stderr else str(e)
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raise RuntimeError(f"ffmpeg error: {msg}")
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def transcribe_file_to_srt(file_obj, language: str = "en"):
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"""Transcribe uploaded file to SRT; compatible with HF Spaces"""
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tmp_dir = Path(tempfile.mkdtemp(prefix="subgen_"))
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# Handle Hugging Face NamedString / Path
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input_path = Path(file_obj.name)
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if not input_path.exists():
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input_path = tmp_dir / Path(file_obj.name).name
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if hasattr(file_obj, "read_bytes"):
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with open(input_path, "wb") as f:
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f.write(file_obj.read_bytes())
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else:
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with open(file_obj.name, "rb") as src, open(input_path, "wb") as dst:
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dst.write(src.read())
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# Extract audio and transcribe
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audio_path = tmp_dir / "audio.wav"
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extract_audio(str(input_path), str(audio_path))
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segments, _ = model.transcribe(str(audio_path), language=language)
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segs = [{"start": s.start, "end": s.end, "text": s.text} for s in segments]
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srt_text = segments_to_srt(segs)
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# Save .srt file
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output_path = OUTPUT_DIR / f"{Path(file_obj.name).stem}.srt"
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with open(output_path, "w", encoding="utf-8") as f:
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f.write(srt_text)
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return str(output_path), "β
Subtitles generated successfully!"
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# -------- Gradio UI --------
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with gr.Blocks(title="AI Subtitle Generator") as demo:
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theme_state = gr.State("light")
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else:
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bg = "linear-gradient(135deg, #fdfbfb, #ebedee)"
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color = "#000000"
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return gr.update(
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value=f"<style>body {{ background: {bg}; color: {color}; }}</style>"
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)
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gr.HTML("<h1 style='text-align:center;'>π¬ AI Subtitle Generator</h1>")
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gr.HTML(
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"<p style='text-align:center;'>Upload a video or audio file to generate English <b>.srt</b> subtitles.</p>"
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)
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style_box = gr.HTML("")
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theme_btn = gr.Button("π Toggle Light/Dark Mode")
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with gr.Row():
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input_file = gr.File(label="Upload video/audio file")
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output_file = gr.File(label="Download .srt file")
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status_box = gr.Textbox(label="Status", interactive=False)
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def on_click(file):
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srt_path, msg = transcribe_file_to_srt(file)
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return srt_path, msg
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theme_btn.click(
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toggle_theme, inputs=[theme_state], outputs=[theme_state]
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).then(apply_theme, inputs=[theme_state], outputs=[style_box])
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generate_btn = gr.Button("Generate Subtitles")
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generate_btn.click(on_click, inputs=[input_file], outputs=[output_file, status_box])
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gr.HTML(
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"<p style='text-align:center;font-size:14px;opacity:0.7;'>Powered by Faster-Whisper + Gradio UI</p>"
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)
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if __name__ == "__main__":
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demo.launch()
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