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Summary
Browse files
app/app.py
CHANGED
@@ -65,16 +65,15 @@ APP = """
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<h3>Journals</h3>
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<pre>
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<code>
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@article{
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author = {Elena
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title = {
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journal = {
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volume = {
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pages = {
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year = {
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doi = {<a href="https://doi.org/10.1016/j.
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}
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@article{ryumina24_eswa,
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author = {Elena Ryumina and Maxim Markitantov and Dmitry Ryumin and Alexey Karpov},
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title = {OCEAN-AI Framework with EmoFormer Cross-Hemiface Attention Approach for Personality Traits Assessment},
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@@ -83,6 +82,15 @@ APP = """
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pages = {122441},
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year = {2024},
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doi = {<a href="https://doi.org/10.1016/j.eswa.2023.122441">https://doi.org/10.1016/j.eswa.2023.122441</a>},
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}
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</code>
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</pre>
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@@ -90,6 +98,13 @@ APP = """
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<h3>Conferences</h3>
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<pre>
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<code>
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@inproceedings{ryumina23_interspeech,
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author = {Elena Ryumina and Dmitry Ryumin and Maxim Markitantov and Heysem Kaya and Alexey Karpov},
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title = {Multimodal Personality Traits Assessment (MuPTA) Corpus: The Impact of Spontaneous and Read Speech},
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<h3>Journals</h3>
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<pre>
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<code>
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@article{ryumina24_prl,
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author = {Ryumina, Elena and Markitantov, Maxim and Ryumin, Dmitry and Karpov, Alexey},
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title = {Gated Siamese Fusion Network based on Multimodal Deep and Hand-Crafted Features for Personality Traits Assessment},
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journal = {Pattern Recognition Letters},
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volume = {185},
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pages = {45--51},
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year = {2024},
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doi = {<a href="https://doi.org/10.1016/j.patrec.2024.07.004">https://doi.org/10.1016/j.patrec.2024.07.004</a>},
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}
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@article{ryumina24_eswa,
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author = {Elena Ryumina and Maxim Markitantov and Dmitry Ryumin and Alexey Karpov},
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title = {OCEAN-AI Framework with EmoFormer Cross-Hemiface Attention Approach for Personality Traits Assessment},
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pages = {122441},
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year = {2024},
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doi = {<a href="https://doi.org/10.1016/j.eswa.2023.122441">https://doi.org/10.1016/j.eswa.2023.122441</a>},
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}
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@article{ryumina22_neurocomputing,
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author = {Elena Ryumina and Denis Dresvyanskiy and Alexey Karpov},
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title = {In Search of a Robust Facial Expressions Recognition Model: A Large-Scale Visual Cross-Corpus Study},
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journal = {Neurocomputing},
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volume = {514},
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pages = {435-450},
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year = {2022},
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doi = {<a href="https://doi.org/10.1016/j.neucom.2022.10.013">https://doi.org/10.1016/j.neucom.2022.10.013</a>},
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}
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</code>
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</pre>
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<h3>Conferences</h3>
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<pre>
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<code>
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@inproceedings{ryumina24_interspeech,
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author = {Elena Ryumina and Dmitry Ryumin and and Alexey Karpov},
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title = {OCEAN-AI: Open Multimodal Framework for Personality Traits Assessment and HR-Processes Automatization},
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year = {2024},
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booktitle = {INTERSPEECH},
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pages = {in press},
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}
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@inproceedings{ryumina23_interspeech,
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author = {Elena Ryumina and Dmitry Ryumin and Maxim Markitantov and Heysem Kaya and Alexey Karpov},
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title = {Multimodal Personality Traits Assessment (MuPTA) Corpus: The Impact of Spontaneous and Read Speech},
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app/description.py
CHANGED
@@ -15,6 +15,10 @@ TEMPLATE = """\
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<img src="https://img.shields.io/badge/version-v{version}-rc0" alt="{version_label}">
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<a href='https://github.com/DmitryRyumin/OCEANAI' target='_blank'><img src='https://img.shields.io/github/stars/DmitryRyumin/OCEANAI?style=flat' alt='GitHub' /></a>
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</div>
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"""
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DESCRIPTIONS = [
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<img src="https://img.shields.io/badge/version-v{version}-rc0" alt="{version_label}">
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<a href='https://github.com/DmitryRyumin/OCEANAI' target='_blank'><img src='https://img.shields.io/github/stars/DmitryRyumin/OCEANAI?style=flat' alt='GitHub' /></a>
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</div>
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The models used in OCEAN-AI were trained on 15-second clips from the ChaLearn First Impression v2 dataset.
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For more reliable predictions, 15-second videos are recommended, but OCEAN-AI can analyze videos of any length.
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Due to limited computational resources on HuggingFace, we provide six 3-second videos as examples.
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"""
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DESCRIPTIONS = [
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app/event_handlers/practical_subtasks.py
CHANGED
@@ -317,10 +317,21 @@ def event_handler_practical_subtasks(
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or practical_subtasks.lower() == "mobile device application categories"
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or practical_subtasks.lower() == "clothing style correlation"
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):
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return (
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practical_subtasks_selected,
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or practical_subtasks.lower() == "mobile device application categories"
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or practical_subtasks.lower() == "clothing style correlation"
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):
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if practical_subtasks.lower() == "car characteristics":
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df_correlation_coefficients = read_csv_file(
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config_data.Links_CAR_CHARACTERISTICS,
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["Trait", "Style and performance", "Safety and practicality"],
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)
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elif practical_subtasks.lower() == "mobile device application categories":
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df_correlation_coefficients = read_csv_file(
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config_data.Links_MDA_CATEGORIES
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)
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elif practical_subtasks.lower() == "clothing style correlation":
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df_correlation_coefficients = read_csv_file(config_data.Links_CLOTHING_SC)
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return (
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practical_subtasks_selected,
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app/oceanai_init.py
CHANGED
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# Загрузка весов аудиомоделей
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url = _b5.weights_for_big5_["audio"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_audio_model_weights_hc(url=url, out=out)
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url = _b5.weights_for_big5_["audio"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_audio_model_weights_nn(url=url, out=out)
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# Формирование видеомоделей
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_ = _b5.load_video_model_hc(lang="en", out=out)
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# Загрузка весов видеомоделей
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url = _b5.weights_for_big5_["video"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_video_model_weights_hc(url=url, out=out)
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url = _b5.weights_for_big5_["video"][corpus]["fe"]["sberdisk"]
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_ = _b5.load_video_model_weights_deep_fe(url=url, out=out)
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url = _b5.weights_for_big5_["video"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_video_model_weights_nn(url=url, out=out)
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# Загрузка словаря с экспертными признаками (текстовая модальность)
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_ = _b5.load_text_features(out=out)
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# Формирование текстовых моделей
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_ = _b5.setup_translation_model() # только для русского языка
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# Загрузка весов текстовых моделей
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url = _b5.weights_for_big5_["text"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_text_model_weights_hc(url=url, out=out)
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url = _b5.weights_for_big5_["text"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_text_model_weights_nn(url=url, out=out)
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# Формирование модели для мультимодального объединения информации
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_ = _b5.load_avt_model_b5(out=out)
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# Загрузка весов модели для мультимодального объединения информации
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url = _b5.weights_for_big5_["avt"][corpus]["b5"]["sberdisk"]
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_ = _b5.load_avt_model_weights_b5(url=url, out=out)
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return _b5
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# Загрузка весов аудиомоделей
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url = _b5.weights_for_big5_["audio"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_audio_model_weights_hc(url=url, out=out, force_reload=False)
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url = _b5.weights_for_big5_["audio"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_audio_model_weights_nn(url=url, out=out, force_reload=False)
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# Формирование видеомоделей
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_ = _b5.load_video_model_hc(lang="en", out=out)
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# Загрузка весов видеомоделей
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url = _b5.weights_for_big5_["video"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_video_model_weights_hc(url=url, out=out, force_reload=False)
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url = _b5.weights_for_big5_["video"][corpus]["fe"]["sberdisk"]
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_ = _b5.load_video_model_weights_deep_fe(url=url, out=out, force_reload=False)
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url = _b5.weights_for_big5_["video"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_video_model_weights_nn(url=url, out=out, force_reload=False)
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# Загрузка словаря с экспертными признаками (текстовая модальность)
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_ = _b5.load_text_features(out=out, force_reload=False)
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# Формирование текстовых моделей
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_ = _b5.setup_translation_model() # только для русского языка
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# Загрузка весов текстовых моделей
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url = _b5.weights_for_big5_["text"][corpus]["hc"]["sberdisk"]
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_ = _b5.load_text_model_weights_hc(url=url, out=out, force_reload=False)
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url = _b5.weights_for_big5_["text"][corpus]["nn"]["sberdisk"]
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_ = _b5.load_text_model_weights_nn(url=url, out=out, force_reload=False)
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# Формирование модели для мультимодального объединения информации
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_ = _b5.load_avt_model_b5(out=out)
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# Загрузка весов модели для мультимодального объединения информации
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url = _b5.weights_for_big5_["avt"][corpus]["b5"]["sberdisk"]
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_ = _b5.load_avt_model_weights_b5(url=url, out=out, force_reload=False)
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return _b5
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video_metadata.yaml
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video_metadata:
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-
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- Emily
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- Taylor
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- "+1 (555) 456-7890"
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2_a6a198e51d073b0.mp4:
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- Michael
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- Brown
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- "+1 (555) 234-5678"
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3_9987232dd677712.mp4:
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- Jack
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- Smith
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video_metadata:
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1_a6a198e51d073b0.mp4:
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- Michael
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- Brown
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- "+1 (555) 234-5678"
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2_9093a4ca3c0c834.mp4:
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- Emily
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- Taylor
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- "+1 (555) 456-7890"
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3_9987232dd677712.mp4:
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- Jack
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- Smith
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videos/{2_a6a198e51d073b0.mp4 → 1_a6a198e51d073b0.mp4}
RENAMED
File without changes
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videos/{1_9093a4ca3c0c834.mp4 → 2_9093a4ca3c0c834.mp4}
RENAMED
File without changes
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