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97 строки
1.9 KiB
Plaintext
97 строки
1.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Video summary and visual question answering"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import ammico"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Currently this module supports only video summarization, but it will be updated in the nearest future"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"video_dict = ammico.find_videos(\n",
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" path=str(\"/insert/your/path/here/\"), # path to the folder with images\n",
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" limit=-1, # -1 means no limit on the number of files, by default it is set to 20\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"model = ammico.MultimodalSummaryModel()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"vid_summary_model = ammico.VideoSummaryDetector(summary_model=model, subdict=video_dict)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"summary_dict = vid_summary_model.analyse_video()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"summary_dict[\"summary\"]"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "ammico-dev",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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