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import gradio as gr |
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from main import calculate_cer_both_versions, read_srt_text |
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from visualize import generate_html_report |
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def process_srt_files(reference_file, hypothesis_file): |
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try: |
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ref_path = reference_file.name if hasattr( |
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reference_file, 'name') else reference_file |
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hyp_path = hypothesis_file.name if hasattr( |
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hypothesis_file, 'name') else hypothesis_file |
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reference_text = read_srt_text(ref_path) |
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hypothesis_text = read_srt_text(hyp_path) |
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metrics_no_punct, metrics_with_punct = calculate_cer_both_versions( |
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ref_path, hyp_path) |
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html_content = generate_html_report( |
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reference_text, hypothesis_text, metrics_no_punct, metrics_with_punct) |
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return html_content |
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except Exception as e: |
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return f"An error occurred: {str(e)}" |
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def load_example(): |
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return "gold.srt", "bert.srt" |
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with gr.Blocks() as iface: |
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gr.Markdown("# SRT File Comparison and CER Calculation") |
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gr.Markdown( |
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"## Please upload the golden reference SRT and the target SRT for calculating the CER.") |
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gr.Markdown( |
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"Note: Only CER is supported at the moment, WER will be added in a future version.") |
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with gr.Row(): |
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ref_file = gr.File(label="Reference (Golden) SRT File") |
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hyp_file = gr.File(label="Target SRT File") |
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with gr.Row(): |
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example_btn = gr.Button("Load Example") |
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process_btn = gr.Button("Get CER", variant="primary") |
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output = gr.HTML(label="Results") |
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process_btn.click( |
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fn=process_srt_files, |
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inputs=[ref_file, hyp_file], |
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outputs=output |
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) |
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example_btn.click( |
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fn=load_example, |
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inputs=None, |
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outputs=[ref_file, hyp_file] |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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