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posts in AI Paper Summary" class="entry-crumb" href="https://www.marktechpost.com/category/tech-news/ai-paper-summary/">AI Paper Summary</a></span> <i class="td-icon-right td-bread-sep td-bred-no-url-last"></i> <span class="td-bred-no-url-last">IBM Research Open-Sources Docling: An AI Tool for High-Precision PDF Document Conversion...</span></div></div> <div class="td-pb-row"> <div class="td-pb-span8 td-main-content" role="main"> <div class="td-ss-main-content"> <div class='ai-viewports ai-viewport-1 ai-insert-2-99612563' style='margin: 8px 0; clear: both;' data-insertion-position='prepend' data-selector='.ai-insert-2-99612563' data-insertion-no-dbg data-code='PGRpdiBjbGFzcz0nY29kZS1ibG9jayBjb2RlLWJsb2NrLTInIHN0eWxlPSdtYXJnaW46IDhweCAwOyBjbGVhcjogYm90aDsnPgo8ZGl2IGNsYXNzPSJ0ZC12aXNpYmxlLWRlc2t0b3AiPgogICAgPGEgaHJlZj0iaHR0cHM6Ly9wcmVkaWJhc2UuY29tL3NtYWxsY29uP3V0bV9tZWRpdW09M3JkcGFydHkmdXRtX3NvdXJjZT1tYXJrdGVjaHBvc3QiPjxpbWcgc3JjPSJodHRwczovL3d3dy5tYXJrdGVjaHBvc3QuY29tL3dwLWNvbnRlbnQvdXBsb2Fkcy8yMDI0LzExL0FkLTcwMC14LTMwMC1TbWFsbENvbi5wbmciIGFsdD0iIiAvPjwvYT48L2Rpdj48L2Rpdj4K' data-block='2'></div> <article id="post-62031" class="post-62031 post type-post status-publish format-standard has-post-thumbnail category-ai-paper-summary category-ai-shorts category-applications category-artificial-intelligence category-editors-pick category-language-model category-new-releases category-open-source category-staff category-tech-news category-technology" itemscope itemtype="https://schema.org/Article"> <div class="td-post-header"> <header class="td-post-title"> <h1 class="entry-title">IBM Research Open-Sources Docling: An AI Tool for High-Precision PDF Document Conversion and Structural Integrity Maintenance Across Complex Layouts</h1> <div class="td-module-meta-info"> <div class="td-post-author-name"><div class="td-author-by">By</div> <a href="https://www.marktechpost.com/author/aswinak/">Aswin Ak</a><div class="td-author-line"> - </div> </div> <span class="td-post-date"><time class="entry-date updated td-module-date" datetime="2024-09-06T12:07:06-07:00" >September 6, 2024</time></span> </div> </header> </div> <div class="td-post-content tagdiv-type"> <div class="swp_social_panel swp_horizontal_panel swp_flat_fresh swp_default_full_color swp_other_full_color swp_individual_full_color scale-100 scale-full_width" data-min-width="1100" data-float-color="#ffffff" data-float="none" data-float-mobile="none" data-transition="slide" data-post-id="62031" ><div class="nc_tweetContainer swp_share_button swp_reddit" data-network="reddit"><a class="nc_tweet swp_share_link" rel="nofollow noreferrer noopener" target="_blank" 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href="https://twitter.com/intent/tweet?text=IBM+Research+Open-Sources+Docling%3A+An+AI+Tool+for+High-Precision+PDF+Document+Conversion+and+Structural+Integrity+Maintenance+Across+Complex+Layouts&url=https%3A%2F%2Fwww.marktechpost.com%2F2024%2F09%2F06%2Fibm-research-open-sources-docling-an-ai-tool-for-high-precision-pdf-document-conversion-and-structural-integrity-maintenance-across-complex-layouts%2F&via=Marktechpost" data-link="https://twitter.com/intent/tweet?text=IBM+Research+Open-Sources+Docling%3A+An+AI+Tool+for+High-Precision+PDF+Document+Conversion+and+Structural+Integrity+Maintenance+Across+Complex+Layouts&url=https%3A%2F%2Fwww.marktechpost.com%2F2024%2F09%2F06%2Fibm-research-open-sources-docling-an-ai-tool-for-high-precision-pdf-document-conversion-and-structural-integrity-maintenance-across-complex-layouts%2F&via=Marktechpost"><span class="swp_count swp_hide"><span class="iconFiller"><span class="spaceManWilly"><i class="sw swp_twitter_icon"></i><span class="swp_share">Tweet</span></span></span></span></a></div><div class="nc_tweetContainer swp_share_button total_shares total_sharesalt" ><span class="swp_count ">0 <span class="swp_label">Shares</span></span></div></div> <p>Document conversion, particularly from PDF to machine-processable formats, has long presented significant challenges due to PDF files’ diverse and often complex nature. These documents, widely used across various industries, frequently need more standardization, resulting in a loss of structural features when optimized for printing. This structural loss complicates the recovery process, as important elements such as tables, figures, and reading order can be misinterpreted or completely lost. As businesses and researchers increasingly rely on digital documents, the need for efficient and accurate conversion tools has become crucial. The advent of advanced AI-driven tools has provided a promising solution to these challenges, enabling better understanding, processing, and extracting content from complex documents.</p> <p>A critical issue in document conversion is the reliable extraction of content from PDFs while preserving the document’s structural integrity. Traditional methods often falter due to the wide variability in PDF formats, leading to problems such as inaccurate table reconstruction, misplaced text, and lost metadata. This problem is technical and practical, as document conversion accuracy directly impacts downstream tasks such as data analysis, search functionality, and information retrieval. Given the growing reliance on digital documents for academic and industrial purposes, ensuring the fidelity of converted content is essential. The problem lies in developing tools that can handle these tasks with the precision required by modern applications, particularly when dealing with large-scale document collections.</p><div class='ai-viewports ai-viewport-1 ai-viewport-3 ai-insert-14-16595454' style='margin: 8px 0; clear: both;' data-insertion-position='prepend' data-selector='.ai-insert-14-16595454' data-insertion-no-dbg data-code='PGRpdiBjbGFzcz0nY29kZS1ibG9jayBjb2RlLWJsb2NrLTE0JyBzdHlsZT0nbWFyZ2luOiA4cHggMDsgY2xlYXI6IGJvdGg7Jz4KPGEgaHJlZj0iaHR0cHM6Ly9wcmVkaWJhc2UuY29tL3NtYWxsY29uP3V0bV9tZWRpdW09M3JkcGFydHkmdXRtX3NvdXJjZT1tYXJrdGVjaHBvc3QiPiDwn6e18J+ntSBNdXN0IEF0dGVuZDogU21hbGxDb246IEZyZWUgVmlydHVhbCBHZW5BSSBDb25mZXJlbmNlIGZ0LiBNZXRhLCBNaXN0cmFsLCBTYWxlc2ZvcmNlLCBIYXJ2ZXkgQUkgJiBtb3JlIChQcm9tb3RlZCk8L2E+PC9kaXY+Cg==' data-block='14'></div> <p>Current tools for PDF conversion, both commercial and open-source, often need to meet the necessary standards of performance and accuracy. Many existing solutions are limited by their dependence on proprietary algorithms and restrictive licenses, which hinder their adaptability and widespread use. Even popular methods struggle with specific tasks, such as accurate table recognition and layout analysis, critical components of high-quality document conversion. For instance, tools like PyPDFium and PyMuPDF have been noted for their shortcomings in processing complex document layouts, resulting in merged text cells or distorted table structures. The lack of an open-source, high-performance solution that can be easily extended and adapted has left a significant gap in the market, particularly for organizations that require reliable tools for large-scale document processing.</p> <p>The AI4K Group at IBM Research introduced <strong>Docling</strong>, an open-source package designed specifically for PDF document conversion. Docling distinguishes itself by leveraging specialized AI models for layout analysis and table structure recognition. These models, including DocLayNet and TableFormer, have been trained on extensive datasets and can handle many document types and formats. Docling is efficient, running on commodity hardware, and versatile, offering configurations for batch processing and interactive use. The tool’s ability to operate with minimal resources while delivering high-quality results makes it an attractive option for academic researchers and commercial enterprises. By bridging the gap between commercial software and open-source tools, Docling provides a robust and adaptable solution for document conversion.</p> <p>The core of Docling’s functionality lies in its processing pipeline, which operates through a series of linear steps to ensure accurate document conversion. Initially, the tool parses the PDF document, extracting text tokens and their geometric coordinates. This is followed by applying AI models that analyze the document’s layout, identify elements such as tables and figures, and reconstruct the original structure with high fidelity. For instance, Docling’s TableFormer model recognizes complex table structures, including those with partial or no borderlines, spanning multiple rows or columns, or containing empty cells. The results of these analyses are then aggregated and post-processed to enhance metadata, determine the document’s language, and correct reading order. This comprehensive approach ensures that the converted document retains its original integrity, whether it is output in JSON or Markdown format.</p><div class='ai-viewports ai-viewport-1 ai-viewport-3 ai-insert-15-83272088' style='margin: 8px 0; clear: both;' data-insertion-position='prepend' data-selector='.ai-insert-15-83272088' data-insertion-no-dbg data-code='PGRpdiBjbGFzcz0nY29kZS1ibG9jayBjb2RlLWJsb2NrLTE1JyBzdHlsZT0nbWFyZ2luOiA4cHggMDsgY2xlYXI6IGJvdGg7Jz4KPGEgaHJlZj0iaHR0cHM6Ly9sYW5kaW5nLmRlZXBzZXQuYWkvZGVlcHNldC1yZWNvZ25pemVkLWFzLWEtZ2FydG5lci1jb29sLXZlbmRvcj91dG1fY2FtcGFpZ249MjQxMC1nYXJ0bmVyLWNvb2wlMjB2ZW5kb3ItcmVwb3J0JnV0bV9zb3VyY2U9bWFya3RlY2hwb3N0JnV0bV9tZWRpdW09bW9iaWxlLWJhbm5lci1hZCI+IPCfk6Xwn5OlIERvd25sb2FkIFJlcG9ydDogMjAyNCBHYXJ0bmVywq4gQ29vbCBWZW5kb3Jz4oSiIGluIEFJIEVuZ2luZWVyaW5nICAoUHJvbW90ZWQpPC9hPjwvZGl2Pgo=' data-block='15'></div> <div class="wp-block-image"> <figure class="aligncenter"><img decoding="async" src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXdjXLmI07GP3EiqKOAK4W16cuezOEI2wHP5TxW6rTGFXXPdsUX9D-XmWLnv1odWpFraDsCMkD26b9fe9kzV6VVVpAm4jMTUW3kl-B6vYhaTNSdiGJe6nOLnHMclFW0f4-mRlbz_-OV8tncTAR7B39OijHbW?key=5F7S4S4QuWvK_v4yy7WMlQ" alt=""/></figure></div> <p>Docling has demonstrated impressive capabilities across various hardware configurations. Tests conducted on a dataset of 225 pages revealed that Docling could process documents with sub-second latency per page on a single CPU. Specifically, on a MacBook Pro M3 Max with 16 cores, Docling processed 92 pages in just 103 seconds using 16 threads, achieving a throughput of 2.45 pages per second. Even on older hardware, such as an Intel Xeon E5-2690, Docling maintained respectable performance, processing 143 pages in 239 seconds with 16 threads. These results highlight Docling’s ability to deliver fast and accurate document conversion, making it a practical choice for environments with varying resource constraints.</p> <div class="wp-block-image"> <figure class="aligncenter size-large is-resized"><img fetchpriority="high" decoding="async" width="1024" height="438" data-attachment-id="62032" data-permalink="https://www.marktechpost.com/2024/09/06/ibm-research-open-sources-docling-an-ai-tool-for-high-precision-pdf-document-conversion-and-structural-integrity-maintenance-across-complex-layouts/screenshot-2024-09-06-at-11-58-23-am/" data-orig-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM.png" data-orig-size="1304,558" data-comments-opened="1" data-image-meta="{"aperture":"0","credit":"","camera":"","caption":"","created_timestamp":"0","copyright":"","focal_length":"0","iso":"0","shutter_speed":"0","title":"","orientation":"0"}" data-image-title="Screenshot 2024-09-06 at 11.58.23 AM" data-image-description="" data-image-caption="" data-medium-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-300x128.png" data-large-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-1024x438.png" src="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-1024x438.png" alt="" class="wp-image-62032" style="width:799px;height:auto" srcset="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-1024x438.png 1024w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-300x128.png 300w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-768x329.png 768w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-982x420.png 982w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-150x64.png 150w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-696x298.png 696w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM-1068x457.png 1068w, https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-06-at-11.58.23-AM.png 1304w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure></div> <p>In conclusion, Docling provides a reliable method for converting complex PDF documents into machine-processable formats by combining advanced AI models with a flexible, open-source platform. Its ability to maintain high performance on standard hardware while ensuring the integrity of converted content makes it an invaluable tool for researchers and commercial users.</p> <hr class="wp-block-separator has-alpha-channel-opacity"/> <p>Check out the <strong><a href="https://arxiv.org/abs/2408.09869" target="_blank" rel="noreferrer noopener">Paper</a> and <a href="https://github.com/DS4SD/docling" target="_blank" rel="noreferrer noopener">GitHub</a>.</strong> All credit for this research goes to the researchers of this project. Also, don’t forget to follow us on <strong><a href="https://twitter.com/Marktechpost">Twitter</a></strong> and <a href="https://www.linkedin.com/company/marktechpost/?viewAsMember=true"><strong>LinkedIn</strong></a>. 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He is pursuing his Dual Degree at the Indian Institute of Technology, Kharagpur. 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Models like BERT and GPT have revolutionized natural language processing,... </div> </div> </div> </div>  <div class="td-block-span12"> <div class="td_module_10 td_module_wrap td-animation-stack"> <div class="td-module-thumb"><a href="https://www.marktechpost.com/2024/11/22/nvidia-introduces-hymba-1-5b-a-hybrid-small-language-model-outperforming-llama-3-2-and-smollm-v2/" rel="bookmark" class="td-image-wrap " title="NVIDIA Introduces Hymba 1.5B: A Hybrid Small Language Model Outperforming Llama 3.2 and SmolLM v2" ><img class="entry-thumb" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAANoAAACWAQMAAACCSQSPAAAAA1BMVEWurq51dlI4AAAAAXRSTlMmkutdmwAAABpJREFUWMPtwQENAAAAwiD7p7bHBwwAAAAg7RD+AAGXD7BoAAAAAElFTkSuQmCC" alt="" title="NVIDIA Introduces Hymba 1.5B: A Hybrid Small Language Model Outperforming Llama 3.2 and SmolLM v2" data-type="image_tag" data-img-url="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-22-at-9.43.46 PM-218x150.png" width="218" height="150" /></a></div> <div class="item-details"> <h3 class="entry-title td-module-title"><a href="https://www.marktechpost.com/2024/11/22/nvidia-introduces-hymba-1-5b-a-hybrid-small-language-model-outperforming-llama-3-2-and-smollm-v2/" rel="bookmark" title="NVIDIA Introduces Hymba 1.5B: A Hybrid Small Language Model Outperforming Llama 3.2 and SmolLM v2">NVIDIA Introduces Hymba 1.5B: A Hybrid Small Language Model Outperforming Llama 3.2 and SmolLM...</a></h3> <div class="td-module-meta-info"> <span class="td-post-author-name"><a href="https://www.marktechpost.com/author/6flvq/">Asif Razzaq</a> <span>-</span> </span> <span class="td-post-date"><time class="entry-date updated td-module-date" datetime="2024-11-22T21:48:05-08:00" >November 22, 2024</time></span> <span class="td-module-comments"><a href="https://www.marktechpost.com/2024/11/22/nvidia-introduces-hymba-1-5b-a-hybrid-small-language-model-outperforming-llama-3-2-and-smollm-v2/#respond">0</a></span> </div> <div class="td-excerpt"> Large language models (LLMs) like GPT-4 and Llama-2 are powerful but require significant computational resources, making them impractical for smaller devices. 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data-type="image_tag" data-img-url="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-21-at-8.46.44 PM-218x150.png" width="218" height="150" /></a></div> <div class="item-details"> <h3 class="entry-title td-module-title"><a href="https://www.marktechpost.com/2024/11/22/meet-balrog-a-novel-ai-benchmark-evaluating-agentic-llm-and-vlm-capabilities-on-long-horizon-interactive-tasks-using-reinforcement-learning-environment/" rel="bookmark" title="Meet ‘BALROG’: A Novel AI Benchmark Evaluating Agentic LLM and VLM Capabilities on Long-Horizon Interactive Tasks Using Reinforcement Learning Environment">Meet ‘BALROG’: A Novel AI Benchmark Evaluating Agentic LLM and VLM Capabilities on Long-Horizon...</a></h3> <div class="td-module-meta-info"> <span class="td-post-author-name"><a href="https://www.marktechpost.com/author/6flvq/">Asif Razzaq</a> <span>-</span> </span> <span class="td-post-date"><time class="entry-date updated td-module-date" 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7004|FreeTAB 7800|FreeTAB 2096|FreeTAB 7.5|FreeTAB 1014|FreeTAB 1001 |FreeTAB 8001|FreeTAB 9706|FreeTAB 9702|FreeTAB 7003|FreeTAB 7002|FreeTAB 1002|FreeTAB 7801|FreeTAB 1331|FreeTAB 1004|FreeTAB 8002|FreeTAB 8014|FreeTAB 9704|FreeTAB 1003",VoninoTablet:"\\b(Argus[ _]?S|Diamond[ _]?79HD|Emerald[ _]?78E|Luna[ _]?70C|Onyx[ _]?S|Onyx[ _]?Z|Orin[ _]?HD|Orin[ _]?S|Otis[ _]?S|SpeedStar[ _]?S|Magnet[ _]?M9|Primus[ _]?94[ _]?3G|Primus[ _]?94HD|Primus[ _]?QS|Android.*\\bQ8\\b|Sirius[ _]?EVO[ _]?QS|Sirius[ _]?QS|Spirit[ _]?S)\\b",ECSTablet:"V07OT2|TM105A|S10OT1|TR10CS1",StorexTablet:"eZee[_']?(Tab|Go)[0-9]+|TabLC7|Looney Tunes Tab",VodafoneTablet:"SmartTab([ ]+)?[0-9]+|SmartTabII10|SmartTabII7|VF-1497|VFD 1400",EssentielBTablet:"Smart[ ']?TAB[ ]+?[0-9]+|Family[ ']?TAB2",RossMoorTablet:"RM-790|RM-997|RMD-878G|RMD-974R|RMT-705A|RMT-701|RME-601|RMT-501|RMT-711",iMobileTablet:"i-mobile i-note",TolinoTablet:"tolino tab [0-9.]+|tolino shine",AudioSonicTablet:"\\bC-22Q|T7-QC|T-17B|T-17P\\b",AMPETablet:"Android.* A78 ",SkkTablet:"Android.* (SKYPAD|PHOENIX|CYCLOPS)",TecnoTablet:"TECNO P9|TECNO DP8D",JXDTablet:"Android.* \\b(F3000|A3300|JXD5000|JXD3000|JXD2000|JXD300B|JXD300|S5800|S7800|S602b|S5110b|S7300|S5300|S602|S603|S5100|S5110|S601|S7100a|P3000F|P3000s|P101|P200s|P1000m|P200m|P9100|P1000s|S6600b|S908|P1000|P300|S18|S6600|S9100)\\b",iJoyTablet:"Tablet (Spirit 7|Essentia|Galatea|Fusion|Onix 7|Landa|Titan|Scooby|Deox|Stella|Themis|Argon|Unique 7|Sygnus|Hexen|Finity 7|Cream|Cream X2|Jade|Neon 7|Neron 7|Kandy|Scape|Saphyr 7|Rebel|Biox|Rebel|Rebel 8GB|Myst|Draco 7|Myst|Tab7-004|Myst|Tadeo Jones|Tablet Boing|Arrow|Draco Dual Cam|Aurix|Mint|Amity|Revolution|Finity 9|Neon 9|T9w|Amity 4GB Dual Cam|Stone 4GB|Stone 8GB|Andromeda|Silken|X2|Andromeda II|Halley|Flame|Saphyr 9,7|Touch 8|Planet|Triton|Unique 10|Hexen 10|Memphis 4GB|Memphis 8GB|Onix 10)",FX2Tablet:"FX2 PAD7|FX2 PAD10",XoroTablet:"KidsPAD 701|PAD[ ]?712|PAD[ ]?714|PAD[ ]?716|PAD[ ]?717|PAD[ ]?718|PAD[ ]?720|PAD[ ]?721|PAD[ ]?722|PAD[ ]?790|PAD[ ]?792|PAD[ ]?900|PAD[ ]?9715D|PAD[ ]?9716DR|PAD[ ]?9718DR|PAD[ ]?9719QR|PAD[ ]?9720QR|TelePAD1030|Telepad1032|TelePAD730|TelePAD731|TelePAD732|TelePAD735Q|TelePAD830|TelePAD9730|TelePAD795|MegaPAD 1331|MegaPAD 1851|MegaPAD 2151",ViewsonicTablet:"ViewPad 10pi|ViewPad 10e|ViewPad 10s|ViewPad E72|ViewPad7|ViewPad E100|ViewPad 7e|ViewSonic VB733|VB100a",VerizonTablet:"QTAQZ3|QTAIR7|QTAQTZ3|QTASUN1|QTASUN2|QTAXIA1",OdysTablet:"LOOX|XENO10|ODYS[ -](Space|EVO|Xpress|NOON)|\\bXELIO\\b|Xelio10Pro|XELIO7PHONETAB|XELIO10EXTREME|XELIOPT2|NEO_QUAD10",CaptivaTablet:"CAPTIVA PAD",IconbitTablet:"NetTAB|NT-3702|NT-3702S|NT-3702S|NT-3603P|NT-3603P|NT-0704S|NT-0704S|NT-3805C|NT-3805C|NT-0806C|NT-0806C|NT-0909T|NT-0909T|NT-0907S|NT-0907S|NT-0902S|NT-0902S",TeclastTablet:"T98 4G|\\bP80\\b|\\bX90HD\\b|X98 Air|X98 Air 3G|\\bX89\\b|P80 3G|\\bX80h\\b|P98 Air|\\bX89HD\\b|P98 3G|\\bP90HD\\b|P89 3G|X98 3G|\\bP70h\\b|P79HD 3G|G18d 3G|\\bP79HD\\b|\\bP89s\\b|\\bA88\\b|\\bP10HD\\b|\\bP19HD\\b|G18 3G|\\bP78HD\\b|\\bA78\\b|\\bP75\\b|G17s 3G|G17h 3G|\\bP85t\\b|\\bP90\\b|\\bP11\\b|\\bP98t\\b|\\bP98HD\\b|\\bG18d\\b|\\bP85s\\b|\\bP11HD\\b|\\bP88s\\b|\\bA80HD\\b|\\bA80se\\b|\\bA10h\\b|\\bP89\\b|\\bP78s\\b|\\bG18\\b|\\bP85\\b|\\bA70h\\b|\\bA70\\b|\\bG17\\b|\\bP18\\b|\\bA80s\\b|\\bA11s\\b|\\bP88HD\\b|\\bA80h\\b|\\bP76s\\b|\\bP76h\\b|\\bP98\\b|\\bA10HD\\b|\\bP78\\b|\\bP88\\b|\\bA11\\b|\\bA10t\\b|\\bP76a\\b|\\bP76t\\b|\\bP76e\\b|\\bP85HD\\b|\\bP85a\\b|\\bP86\\b|\\bP75HD\\b|\\bP76v\\b|\\bA12\\b|\\bP75a\\b|\\bA15\\b|\\bP76Ti\\b|\\bP81HD\\b|\\bA10\\b|\\bT760VE\\b|\\bT720HD\\b|\\bP76\\b|\\bP73\\b|\\bP71\\b|\\bP72\\b|\\bT720SE\\b|\\bC520Ti\\b|\\bT760\\b|\\bT720VE\\b|T720-3GE|T720-WiFi",OndaTablet:"\\b(V975i|Vi30|VX530|V701|Vi60|V701s|Vi50|V801s|V719|Vx610w|VX610W|V819i|Vi10|VX580W|Vi10|V711s|V813|V811|V820w|V820|Vi20|V711|VI30W|V712|V891w|V972|V819w|V820w|Vi60|V820w|V711|V813s|V801|V819|V975s|V801|V819|V819|V818|V811|V712|V975m|V101w|V961w|V812|V818|V971|V971s|V919|V989|V116w|V102w|V973|Vi40)\\b[\\s]+|V10 \\b4G\\b",JaytechTablet:"TPC-PA762",BlaupunktTablet:"Endeavour 800NG|Endeavour 1010",DigmaTablet:"\\b(iDx10|iDx9|iDx8|iDx7|iDxD7|iDxD8|iDsQ8|iDsQ7|iDsQ8|iDsD10|iDnD7|3TS804H|iDsQ11|iDj7|iDs10)\\b",EvolioTablet:"ARIA_Mini_wifi|Aria[ _]Mini|Evolio X10|Evolio X7|Evolio X8|\\bEvotab\\b|\\bNeura\\b",LavaTablet:"QPAD E704|\\bIvoryS\\b|E-TAB IVORY|\\bE-TAB\\b",AocTablet:"MW0811|MW0812|MW0922|MTK8382|MW1031|MW0831|MW0821|MW0931|MW0712",MpmanTablet:"MP11 OCTA|MP10 OCTA|MPQC1114|MPQC1004|MPQC994|MPQC974|MPQC973|MPQC804|MPQC784|MPQC780|\\bMPG7\\b|MPDCG75|MPDCG71|MPDC1006|MP101DC|MPDC9000|MPDC905|MPDC706HD|MPDC706|MPDC705|MPDC110|MPDC100|MPDC99|MPDC97|MPDC88|MPDC8|MPDC77|MP709|MID701|MID711|MID170|MPDC703|MPQC1010",CelkonTablet:"CT695|CT888|CT[\\s]?910|CT7 Tab|CT9 Tab|CT3 Tab|CT2 Tab|CT1 Tab|C820|C720|\\bCT-1\\b",WolderTablet:"miTab \\b(DIAMOND|SPACE|BROOKLYN|NEO|FLY|MANHATTAN|FUNK|EVOLUTION|SKY|GOCAR|IRON|GENIUS|POP|MINT|EPSILON|BROADWAY|JUMP|HOP|LEGEND|NEW AGE|LINE|ADVANCE|FEEL|FOLLOW|LIKE|LINK|LIVE|THINK|FREEDOM|CHICAGO|CLEVELAND|BALTIMORE-GH|IOWA|BOSTON|SEATTLE|PHOENIX|DALLAS|IN 101|MasterChef)\\b",MediacomTablet:"M-MPI10C3G|M-SP10EG|M-SP10EGP|M-SP10HXAH|M-SP7HXAH|M-SP10HXBH|M-SP8HXAH|M-SP8MXA",MiTablet:"\\bMI PAD\\b|\\bHM NOTE 1W\\b",NibiruTablet:"Nibiru M1|Nibiru Jupiter One",NexoTablet:"NEXO NOVA|NEXO 10|NEXO AVIO|NEXO FREE|NEXO GO|NEXO EVO|NEXO 3G|NEXO SMART|NEXO KIDDO|NEXO MOBI",LeaderTablet:"TBLT10Q|TBLT10I|TBL-10WDKB|TBL-10WDKBO2013|TBL-W230V2|TBL-W450|TBL-W500|SV572|TBLT7I|TBA-AC7-8G|TBLT79|TBL-8W16|TBL-10W32|TBL-10WKB|TBL-W100",UbislateTablet:"UbiSlate[\\s]?7C",PocketBookTablet:"Pocketbook",KocasoTablet:"\\b(TB-1207)\\b",HisenseTablet:"\\b(F5281|E2371)\\b",Hudl:"Hudl HT7S3|Hudl 2",TelstraTablet:"T-Hub2",GenericTablet:"Android.*\\b97D\\b|Tablet(?!.*PC)|BNTV250A|MID-WCDMA|LogicPD Zoom2|\\bA7EB\\b|CatNova8|A1_07|CT704|CT1002|\\bM721\\b|rk30sdk|\\bEVOTAB\\b|M758A|ET904|ALUMIUM10|Smartfren Tab|Endeavour 1010|Tablet-PC-4|Tagi Tab|\\bM6pro\\b|CT1020W|arc 10HD|\\bTP750\\b|\\bQTAQZ3\\b|WVT101|TM1088|KT107"},oss:{AndroidOS:"Android",BlackBerryOS:"blackberry|\\bBB10\\b|rim tablet os",PalmOS:"PalmOS|avantgo|blazer|elaine|hiptop|palm|plucker|xiino",SymbianOS:"Symbian|SymbOS|Series60|Series40|SYB-[0-9]+|\\bS60\\b",WindowsMobileOS:"Windows CE.*(PPC|Smartphone|Mobile|[0-9]{3}x[0-9]{3})|Windows Mobile|Windows Phone [0-9.]+|WCE;",WindowsPhoneOS:"Windows Phone 10.0|Windows Phone 8.1|Windows Phone 8.0|Windows Phone OS|XBLWP7|ZuneWP7|Windows NT 6.[23]; ARM;",iOS:"\\biPhone.*Mobile|\\biPod|\\biPad|AppleCoreMedia",iPadOS:"CPU OS 13",SailfishOS:"Sailfish",MeeGoOS:"MeeGo",MaemoOS:"Maemo",JavaOS:"J2ME/|\\bMIDP\\b|\\bCLDC\\b",webOS:"webOS|hpwOS",badaOS:"\\bBada\\b",BREWOS:"BREW"},uas:{Chrome:"\\bCrMo\\b|CriOS|Android.*Chrome/[.0-9]* (Mobile)?",Dolfin:"\\bDolfin\\b",Opera:"Opera.*Mini|Opera.*Mobi|Android.*Opera|Mobile.*OPR/[0-9.]+$|Coast/[0-9.]+",Skyfire:"Skyfire",Edge:"\\bEdgiOS\\b|Mobile Safari/[.0-9]* Edge",IE:"IEMobile|MSIEMobile",Firefox:"fennec|firefox.*maemo|(Mobile|Tablet).*Firefox|Firefox.*Mobile|FxiOS",Bolt:"bolt",TeaShark:"teashark",Blazer:"Blazer",Safari:"Version((?!\\bEdgiOS\\b).)*Mobile.*Safari|Safari.*Mobile|MobileSafari",WeChat:"\\bMicroMessenger\\b",UCBrowser:"UC.*Browser|UCWEB",baiduboxapp:"baiduboxapp",baidubrowser:"baidubrowser",DiigoBrowser:"DiigoBrowser",Mercury:"\\bMercury\\b",ObigoBrowser:"Obigo",NetFront:"NF-Browser",GenericBrowser:"NokiaBrowser|OviBrowser|OneBrowser|TwonkyBeamBrowser|SEMC.*Browser|FlyFlow|Minimo|NetFront|Novarra-Vision|MQQBrowser|MicroMessenger",PaleMoon:"Android.*PaleMoon|Mobile.*PaleMoon"},props:{Mobile:"Mobile/[VER]",Build:"Build/[VER]",Version:"Version/[VER]",VendorID:"VendorID/[VER]",iPad:"iPad.*CPU[a-z ]+[VER]",iPhone:"iPhone.*CPU[a-z ]+[VER]",iPod:"iPod.*CPU[a-z ]+[VER]",Kindle:"Kindle/[VER]",Chrome:["Chrome/[VER]","CriOS/[VER]","CrMo/[VER]"],Coast:["Coast/[VER]"],Dolfin:"Dolfin/[VER]",Firefox:["Firefox/[VER]","FxiOS/[VER]"],Fennec:"Fennec/[VER]",Edge:"Edge/[VER]",IE:["IEMobile/[VER];","IEMobile [VER]","MSIE [VER];","Trident/[0-9.]+;.*rv:[VER]"],NetFront:"NetFront/[VER]",NokiaBrowser:"NokiaBrowser/[VER]",Opera:[" OPR/[VER]","Opera Mini/[VER]","Version/[VER]"],"Opera Mini":"Opera Mini/[VER]","Opera Mobi":"Version/[VER]",UCBrowser:["UCWEB[VER]","UC.*Browser/[VER]"],MQQBrowser:"MQQBrowser/[VER]",MicroMessenger:"MicroMessenger/[VER]",baiduboxapp:"baiduboxapp/[VER]",baidubrowser:"baidubrowser/[VER]",SamsungBrowser:"SamsungBrowser/[VER]",Iron:"Iron/[VER]",Safari:["Version/[VER]","Safari/[VER]"],Skyfire:"Skyfire/[VER]",Tizen:"Tizen/[VER]",Webkit:"webkit[ /][VER]",PaleMoon:"PaleMoon/[VER]",SailfishBrowser:"SailfishBrowser/[VER]",Gecko:"Gecko/[VER]",Trident:"Trident/[VER]",Presto:"Presto/[VER]",Goanna:"Goanna/[VER]",iOS:" \\bi?OS\\b [VER][ ;]{1}",Android:"Android [VER]",Sailfish:"Sailfish [VER]",BlackBerry:["BlackBerry[\\w]+/[VER]","BlackBerry.*Version/[VER]","Version/[VER]"],BREW:"BREW [VER]",Java:"Java/[VER]","Windows Phone OS":["Windows Phone OS [VER]","Windows Phone [VER]"],"Windows Phone":"Windows Phone [VER]","Windows CE":"Windows CE/[VER]","Windows NT":"Windows NT [VER]",Symbian:["SymbianOS/[VER]","Symbian/[VER]"],webOS:["webOS/[VER]","hpwOS/[VER];"]},utils:{Bot:"Googlebot|facebookexternalhit|Google-AMPHTML|s~amp-validator|AdsBot-Google|Google Keyword Suggestion|Facebot|YandexBot|YandexMobileBot|bingbot|ia_archiver|AhrefsBot|Ezooms|GSLFbot|WBSearchBot|Twitterbot|TweetmemeBot|Twikle|PaperLiBot|Wotbox|UnwindFetchor|Exabot|MJ12bot|YandexImages|TurnitinBot|Pingdom|contentkingapp|AspiegelBot",MobileBot:"Googlebot-Mobile|AdsBot-Google-Mobile|YahooSeeker/M1A1-R2D2",DesktopMode:"WPDesktop",TV:"SonyDTV|HbbTV",WebKit:"(webkit)[ /]([\\w.]+)",Console:"\\b(Nintendo|Nintendo WiiU|Nintendo 3DS|Nintendo Switch|PLAYSTATION|Xbox)\\b",Watch:"SM-V700"}},g.detectMobileBrowsers={fullPattern:/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i, shortPattern:/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i,tabletPattern:/android|ipad|playbook|silk/i};var h,i=Object.prototype.hasOwnProperty;return g.FALLBACK_PHONE="UnknownPhone",g.FALLBACK_TABLET="UnknownTablet",g.FALLBACK_MOBILE="UnknownMobile",h="isArray"in Array?Array.isArray:function(a){return"[object Array]"===Object.prototype.toString.call(a)},function(){var a,b,c,e,f,j,k=g.mobileDetectRules;for(a in k.props)if(i.call(k.props,a)){for(b=k.props[a],h(b)||(b=[b]),f=b.length,e=0;e<f;++e)c=b[e],j=c.indexOf("[VER]"),j>=0&&(c=c.substring(0,j)+"([\\w._\\+]+)"+c.substring(j+5)),b[e]=new RegExp(c,"i");k.props[a]=b}d(k.oss),d(k.phones),d(k.tablets),d(k.uas),d(k.utils),k.oss0={WindowsPhoneOS:k.oss.WindowsPhoneOS,WindowsMobileOS:k.oss.WindowsMobileOS}}(),g.findMatch=function(a,b){for(var c in a)if(i.call(a,c)&&a[c].test(b))return c;return null},g.findMatches=function(a,b){var c=[];for(var d in a)i.call(a,d)&&a[d].test(b)&&c.push(d);return c},g.getVersionStr=function(a,b){var c,d,e,f,h=g.mobileDetectRules.props;if(i.call(h,a))for(c=h[a],e=c.length,d=0;d<e;++d)if(f=c[d].exec(b),null!==f)return f[1];return null},g.getVersion=function(a,b){var c=g.getVersionStr(a,b);return c?g.prepareVersionNo(c):NaN},g.prepareVersionNo=function(a){var b;return b=a.split(/[a-z._ \/\-]/i),1===b.length&&(a=b[0]),b.length>1&&(a=b[0]+".",b.shift(),a+=b.join("")),Number(a)},g.isMobileFallback=function(a){return g.detectMobileBrowsers.fullPattern.test(a)||g.detectMobileBrowsers.shortPattern.test(a.substr(0,4))},g.isTabletFallback=function(a){return g.detectMobileBrowsers.tabletPattern.test(a)},g.prepareDetectionCache=function(a,c,d){if(a.mobile===b){var 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