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Parent(s):
70b5707
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app.py
CHANGED
@@ -1,5 +1,5 @@
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import torch
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import gradio as gr
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from torchaudio.sox_effects import apply_effects_file
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from transformers import AutoFeatureExtractor, AutoModelForAudioXVector
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@@ -8,7 +8,9 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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STYLE = """
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css" integrity="sha256-YvdLHPgkqJ8DVUxjjnGVlMMJtNimJ6dYkowFFvp4kKs=" crossorigin="anonymous">
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"""
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OUTPUT_OK =
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<div class="container">
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<div class="row"><h1 style="text-align: center">The speakers are</h1></div>
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<div class="row"><h1 class="display-1 text-success" style="text-align: center">{:.1f}%</h1></div>
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@@ -17,7 +19,10 @@ OUTPUT_OK = STYLE + """
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<div class="row"><small style="text-align: center">(You must get at least 85% to be considered the same person)</small><div class="row">
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</div>
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"""
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<div class="container">
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<div class="row"><h1 style="text-align: center">The speakers are</h1></div>
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<div class="row"><h1 class="display-1 text-danger" style="text-align: center">{:.1f}%</h1></div>
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@@ -26,14 +31,15 @@ OUTPUT_FAIL = STYLE + """
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<div class="row"><small style="text-align: center">(You must get at least 85% to be considered the same person)</small><div class="row">
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</div>
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"""
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EFFECTS = [
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[
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["channels", "1"],
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["rate", "16000"],
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["gain", "-1.0"],
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["silence", "1", "0.1", "0.1%", "-1", "0.1", "0.1%"],
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[
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]
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THRESHOLD = 0.85
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@@ -88,6 +94,27 @@ article = (
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"<a href='https://www.danielpovey.com/files/2018_icassp_xvectors.pdf' target='_blank'>π X-Vector paper</a>"
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"</p>"
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)
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interface = gr.Interface(
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fn=similarity_fn,
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@@ -100,26 +127,6 @@ interface = gr.Interface(
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theme="huggingface",
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allow_flagging=False,
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live=False,
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examples=
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["samples/cate_blanch.mp3", "samples/cate_blanch_2.mp3"],
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["samples/cate_blanch.mp3", "samples/cate_blanch_3.mp3"],
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["samples/cate_blanch_2.mp3", "samples/cate_blanch_3.mp3"],
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["samples/heath_ledger.mp3", "samples/heath_ledger_2.mp3"],
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["samples/heath_ledger.mp3", "samples/heath_ledger_3.mp3"],
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["samples/heath_ledger_2.mp3", "samples/heath_ledger_3.mp3"],
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["samples/russel_crowe.mp3", "samples/russel_crowe_2.mp3"],
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["samples/cate_blanch.mp3", "samples/kirsten_dunst.wav"],
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["samples/russel_crowe.mp3", "samples/kirsten_dunst.wav"],
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["samples/russel_crowe_2.mp3", "samples/kirsten_dunst.wav"],
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["samples/leonardo_dicaprio.mp3", "samples/denzel_washington.mp3"],
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["samples/heath_ledger.mp3", "samples/denzel_washington.mp3"],
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["samples/heath_ledger_2.mp3", "samples/denzel_washington.mp3"],
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["samples/leonardo_dicaprio.mp3", "samples/russel_crowe.mp3"],
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["samples/leonardo_dicaprio.mp3", "samples/russel_crowe_2.mp3"],
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["samples/naomi_watts.mp3", "samples/denzel_washington.mp3"],
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["samples/naomi_watts.mp3", "samples/leonardo_dicaprio.mp3"],
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["samples/naomi_watts.mp3", "samples/cate_blanch_2.mp3"],
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["samples/naomi_watts.mp3", "samples/kirsten_dunst.wav"],
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]
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)
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interface.launch(enable_queue=True)
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import gradio as gr
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import torch
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from torchaudio.sox_effects import apply_effects_file
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from transformers import AutoFeatureExtractor, AutoModelForAudioXVector
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STYLE = """
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css" integrity="sha256-YvdLHPgkqJ8DVUxjjnGVlMMJtNimJ6dYkowFFvp4kKs=" crossorigin="anonymous">
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"""
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OUTPUT_OK = (
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STYLE
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+ """
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<div class="container">
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<div class="row"><h1 style="text-align: center">The speakers are</h1></div>
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<div class="row"><h1 class="display-1 text-success" style="text-align: center">{:.1f}%</h1></div>
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<div class="row"><small style="text-align: center">(You must get at least 85% to be considered the same person)</small><div class="row">
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</div>
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"""
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)
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OUTPUT_FAIL = (
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STYLE
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+ """
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<div class="container">
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<div class="row"><h1 style="text-align: center">The speakers are</h1></div>
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<div class="row"><h1 class="display-1 text-danger" style="text-align: center">{:.1f}%</h1></div>
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<div class="row"><small style="text-align: center">(You must get at least 85% to be considered the same person)</small><div class="row">
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</div>
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"""
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)
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EFFECTS = [
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["remix", "-"],
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["channels", "1"],
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["rate", "16000"],
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["gain", "-1.0"],
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["silence", "1", "0.1", "0.1%", "-1", "0.1", "0.1%"],
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["trim", "0", "10"],
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]
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THRESHOLD = 0.85
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"<a href='https://www.danielpovey.com/files/2018_icassp_xvectors.pdf' target='_blank'>π X-Vector paper</a>"
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"</p>"
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)
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examples = [
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["samples/cate_blanch.mp3", "samples/cate_blanch_2.mp3"],
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["samples/cate_blanch.mp3", "samples/cate_blanch_3.mp3"],
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["samples/cate_blanch_2.mp3", "samples/cate_blanch_3.mp3"],
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["samples/heath_ledger.mp3", "samples/heath_ledger_2.mp3"],
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["samples/heath_ledger.mp3", "samples/heath_ledger_3.mp3"],
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["samples/heath_ledger_2.mp3", "samples/heath_ledger_3.mp3"],
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["samples/russel_crowe.mp3", "samples/russel_crowe_2.mp3"],
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["samples/cate_blanch.mp3", "samples/kirsten_dunst.wav"],
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["samples/russel_crowe.mp3", "samples/kirsten_dunst.wav"],
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["samples/russel_crowe_2.mp3", "samples/kirsten_dunst.wav"],
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["samples/leonardo_dicaprio.mp3", "samples/denzel_washington.mp3"],
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["samples/heath_ledger.mp3", "samples/denzel_washington.mp3"],
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["samples/heath_ledger_2.mp3", "samples/denzel_washington.mp3"],
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["samples/leonardo_dicaprio.mp3", "samples/russel_crowe.mp3"],
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["samples/leonardo_dicaprio.mp3", "samples/russel_crowe_2.mp3"],
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["samples/naomi_watts.mp3", "samples/denzel_washington.mp3"],
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["samples/naomi_watts.mp3", "samples/leonardo_dicaprio.mp3"],
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["samples/naomi_watts.mp3", "samples/cate_blanch_2.mp3"],
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["samples/naomi_watts.mp3", "samples/kirsten_dunst.wav"],
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]
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interface = gr.Interface(
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fn=similarity_fn,
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theme="huggingface",
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allow_flagging=False,
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live=False,
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examples=examples,
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)
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interface.launch(enable_queue=True)
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