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Add AzureReadTextDetection component. (#131)
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‎docs/docs/index.md‎

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| Detection/Tracking | Motion | SuBSENSE w/ STRUCK
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| Detection/Tracking | License Plate | OpenALPR
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| Detection | Speech | Sphinx
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| Detection | Speech | Azure Cognitive Services
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| Detection | Speech | Azure Cognitive Services Batch Transcription API
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| Detection | Scene | OpenCV
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| Detection | Classification | OpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color)
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| Detection/Tracking | Classification | OpenCV DNN (YOLO)
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| Detection | Text Region | EAST
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| Detection | Text (OCR) | Apache Tika
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| Detection | Text (OCR) | Tesseract OCR
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| Detection | Text (OCR) | Azure Cognitive Services
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| Detection | Form Structure (with OCR) | Azure Cognitive Services
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| Detection | Text (OCR) | Azure Cognitive Services Computer Vision API (OCR endpoint)
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| Detection | Text (OCR) | Azure Cognitive Services Read API
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| Detection | Form Structure (with OCR) | Azure Cognitive Services Form Recognizer API
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| Detection | Keywords | Boost Regular Expressions
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| Detection | Image (from document) | Apache Tika
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| Translation | Language | Azure Cognitive Services
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| Translation | Language | Azure Cognitive Services Translate API
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The OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.

‎docs/site/index.html‎

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<td>Detection</td>
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<td>Azure Cognitive Services</td>
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<td>Azure Cognitive Services Batch Transcription API</td>
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<td>Detection</td>
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<td>Azure Cognitive Services</td>
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<td>Azure Cognitive Services Computer Vision API (OCR endpoint)</td>
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<td>Detection</td>
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<td>Text (OCR)</td>
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<td>Azure Cognitive Services Read API</td>
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<td>Detection</td>
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<td>Form Structure (with OCR)</td>
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<td>Azure Cognitive Services</td>
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<td>Azure Cognitive Services Form Recognizer API</td>
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<td>Azure Cognitive Services</td>
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<!--
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Build Date UTC : 2021-06-22 18:36:37
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‎docs/site/mkdocs/search_index.json‎

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"docs": [
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{
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"text": "NOTICE:\n This software (or technical data) was produced for the U.S. Government under contract, and is subject to the\nRights in Data-General Clause 52.227-14, Alt. IV (DEC 2007). Copyright 2021 The MITRE Corporation. All Rights Reserved.\n\n\nOverview\n\n\nThere are numerous video and image exploitation capabilities available today. The Open Media Processing Framework (OpenMPF) provides a framework for chaining, combining, or replacing individual components for the purpose of experimentation and comparison.\n\n\nOpenMPF is a non-proprietary, scalable framework that permits practitioners and researchers to construct video, imagery, and audio exploitation capabilities using the available third-party components. Using OpenMPF, one can extract targeted entities in large-scale data environments, such as face and object detection.\n\n\nFor those developing new exploitation capabilities, OpenMPF exposes a set of Application Program Interfaces (APIs) for extending media analytics functionality. The APIs allow integrators to introduce new algorithms capable of detecting new targeted entity types. For example, a backpack detection algorithm could be integrated into an OpenMPF instance. OpenMPF does not restrict the number of algorithms that can operate on a given media file, permitting researchers, practitioners, and developers to explore arbitrarily complex composites of exploitation algorithms.\n\n\nA list of algorithms currently integrated into the OpenMPF as distributed processing components is shown here:\n\n\n\n\n\n\n\n\nOperation\n\n\nObject Type\n\n\nFramework\n\n\n\n\n\n\n\n\n\n\nDetection/Tracking\n\n\nFace\n\n\nLBP-Based OpenCV\n\n\n\n\n\n\nDetection/Tracking\n\n\nFace\n\n\nDlib\n\n\n\n\n\n\nDetection/Tracking\n\n\nPerson\n\n\nHOG-Based OpenCV\n\n\n\n\n\n\nDetection/Tracking\n\n\nMotion\n\n\nMOG w/ STRUCK\n\n\n\n\n\n\nDetection/Tracking\n\n\nMotion\n\n\nSuBSENSE w/ STRUCK\n\n\n\n\n\n\nDetection/Tracking\n\n\nLicense Plate\n\n\nOpenALPR\n\n\n\n\n\n\nDetection\n\n\nSpeech\n\n\nSphinx\n\n\n\n\n\n\nDetection\n\n\nSpeech\n\n\nAzure Cognitive Services\n\n\n\n\n\n\nDetection\n\n\nScene\n\n\nOpenCV\n\n\n\n\n\n\nDetection\n\n\nClassification\n\n\nOpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification\n\n\nOpenCV DNN (YOLO)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification\n\n\nDarknet (YOLO)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification/Features\n\n\nTensorRT (COCO classes)\n\n\n\n\n\n\nDetection\n\n\nText Region\n\n\nEAST\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nApache Tika\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nTesseract OCR\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nAzure Cognitive Services\n\n\n\n\n\n\nDetection\n\n\nForm Structure (with OCR)\n\n\nAzure Cognitive Services\n\n\n\n\n\n\nDetection\n\n\nKeywords\n\n\nBoost Regular Expressions\n\n\n\n\n\n\nDetection\n\n\nImage (from document)\n\n\nApache Tika\n\n\n\n\n\n\nTranslation\n\n\nLanguage\n\n\nAzure Cognitive Services\n\n\n\n\n\n\n\n\nThe OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.",
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"text": "NOTICE:\n This software (or technical data) was produced for the U.S. Government under contract, and is subject to the\nRights in Data-General Clause 52.227-14, Alt. IV (DEC 2007). Copyright 2021 The MITRE Corporation. All Rights Reserved.\n\n\nOverview\n\n\nThere are numerous video and image exploitation capabilities available today. The Open Media Processing Framework (OpenMPF) provides a framework for chaining, combining, or replacing individual components for the purpose of experimentation and comparison.\n\n\nOpenMPF is a non-proprietary, scalable framework that permits practitioners and researchers to construct video, imagery, and audio exploitation capabilities using the available third-party components. Using OpenMPF, one can extract targeted entities in large-scale data environments, such as face and object detection.\n\n\nFor those developing new exploitation capabilities, OpenMPF exposes a set of Application Program Interfaces (APIs) for extending media analytics functionality. The APIs allow integrators to introduce new algorithms capable of detecting new targeted entity types. For example, a backpack detection algorithm could be integrated into an OpenMPF instance. OpenMPF does not restrict the number of algorithms that can operate on a given media file, permitting researchers, practitioners, and developers to explore arbitrarily complex composites of exploitation algorithms.\n\n\nA list of algorithms currently integrated into the OpenMPF as distributed processing components is shown here:\n\n\n\n\n\n\n\n\nOperation\n\n\nObject Type\n\n\nFramework\n\n\n\n\n\n\n\n\n\n\nDetection/Tracking\n\n\nFace\n\n\nLBP-Based OpenCV\n\n\n\n\n\n\nDetection/Tracking\n\n\nFace\n\n\nDlib\n\n\n\n\n\n\nDetection/Tracking\n\n\nPerson\n\n\nHOG-Based OpenCV\n\n\n\n\n\n\nDetection/Tracking\n\n\nMotion\n\n\nMOG w/ STRUCK\n\n\n\n\n\n\nDetection/Tracking\n\n\nMotion\n\n\nSuBSENSE w/ STRUCK\n\n\n\n\n\n\nDetection/Tracking\n\n\nLicense Plate\n\n\nOpenALPR\n\n\n\n\n\n\nDetection\n\n\nSpeech\n\n\nSphinx\n\n\n\n\n\n\nDetection\n\n\nSpeech\n\n\nAzure Cognitive Services Batch Transcription API\n\n\n\n\n\n\nDetection\n\n\nScene\n\n\nOpenCV\n\n\n\n\n\n\nDetection\n\n\nClassification\n\n\nOpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification\n\n\nOpenCV DNN (YOLO)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification\n\n\nDarknet (YOLO)\n\n\n\n\n\n\nDetection/Tracking\n\n\nClassification/Features\n\n\nTensorRT (COCO classes)\n\n\n\n\n\n\nDetection\n\n\nText Region\n\n\nEAST\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nApache Tika\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nTesseract OCR\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nAzure Cognitive Services Computer Vision API (OCR endpoint)\n\n\n\n\n\n\nDetection\n\n\nText (OCR)\n\n\nAzure Cognitive Services Read API\n\n\n\n\n\n\nDetection\n\n\nForm Structure (with OCR)\n\n\nAzure Cognitive Services Form Recognizer API\n\n\n\n\n\n\nDetection\n\n\nKeywords\n\n\nBoost Regular Expressions\n\n\n\n\n\n\nDetection\n\n\nImage (from document)\n\n\nApache Tika\n\n\n\n\n\n\nTranslation\n\n\nLanguage\n\n\nAzure Cognitive Services Translate API\n\n\n\n\n\n\n\n\nThe OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.",
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"title": "Home"
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"location": "/index.html#overview",
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"text": "There are numerous video and image exploitation capabilities available today. The Open Media Processing Framework (OpenMPF) provides a framework for chaining, combining, or replacing individual components for the purpose of experimentation and comparison. OpenMPF is a non-proprietary, scalable framework that permits practitioners and researchers to construct video, imagery, and audio exploitation capabilities using the available third-party components. Using OpenMPF, one can extract targeted entities in large-scale data environments, such as face and object detection. For those developing new exploitation capabilities, OpenMPF exposes a set of Application Program Interfaces (APIs) for extending media analytics functionality. The APIs allow integrators to introduce new algorithms capable of detecting new targeted entity types. For example, a backpack detection algorithm could be integrated into an OpenMPF instance. OpenMPF does not restrict the number of algorithms that can operate on a given media file, permitting researchers, practitioners, and developers to explore arbitrarily complex composites of exploitation algorithms. A list of algorithms currently integrated into the OpenMPF as distributed processing components is shown here: Operation Object Type Framework Detection/Tracking Face LBP-Based OpenCV Detection/Tracking Face Dlib Detection/Tracking Person HOG-Based OpenCV Detection/Tracking Motion MOG w/ STRUCK Detection/Tracking Motion SuBSENSE w/ STRUCK Detection/Tracking License Plate OpenALPR Detection Speech Sphinx Detection Speech Azure Cognitive Services Detection Scene OpenCV Detection Classification OpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color) Detection/Tracking Classification OpenCV DNN (YOLO) Detection/Tracking Classification Darknet (YOLO) Detection/Tracking Classification/Features TensorRT (COCO classes) Detection Text Region EAST Detection Text (OCR) Apache Tika Detection Text (OCR) Tesseract OCR Detection Text (OCR) Azure Cognitive Services Detection Form Structure (with OCR) Azure Cognitive Services Detection Keywords Boost Regular Expressions Detection Image (from document) Apache Tika Translation Language Azure Cognitive Services The OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.",
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"text": "There are numerous video and image exploitation capabilities available today. The Open Media Processing Framework (OpenMPF) provides a framework for chaining, combining, or replacing individual components for the purpose of experimentation and comparison. OpenMPF is a non-proprietary, scalable framework that permits practitioners and researchers to construct video, imagery, and audio exploitation capabilities using the available third-party components. Using OpenMPF, one can extract targeted entities in large-scale data environments, such as face and object detection. For those developing new exploitation capabilities, OpenMPF exposes a set of Application Program Interfaces (APIs) for extending media analytics functionality. The APIs allow integrators to introduce new algorithms capable of detecting new targeted entity types. For example, a backpack detection algorithm could be integrated into an OpenMPF instance. OpenMPF does not restrict the number of algorithms that can operate on a given media file, permitting researchers, practitioners, and developers to explore arbitrarily complex composites of exploitation algorithms. A list of algorithms currently integrated into the OpenMPF as distributed processing components is shown here: Operation Object Type Framework Detection/Tracking Face LBP-Based OpenCV Detection/Tracking Face Dlib Detection/Tracking Person HOG-Based OpenCV Detection/Tracking Motion MOG w/ STRUCK Detection/Tracking Motion SuBSENSE w/ STRUCK Detection/Tracking License Plate OpenALPR Detection Speech Sphinx Detection Speech Azure Cognitive Services Batch Transcription API Detection Scene OpenCV Detection Classification OpenCV DNN (GoogLeNet, Yahoo NSFW, vehicle color) Detection/Tracking Classification OpenCV DNN (YOLO) Detection/Tracking Classification Darknet (YOLO) Detection/Tracking Classification/Features TensorRT (COCO classes) Detection Text Region EAST Detection Text (OCR) Apache Tika Detection Text (OCR) Tesseract OCR Detection Text (OCR) Azure Cognitive Services Computer Vision API (OCR endpoint) Detection Text (OCR) Azure Cognitive Services Read API Detection Form Structure (with OCR) Azure Cognitive Services Form Recognizer API Detection Keywords Boost Regular Expressions Detection Image (from document) Apache Tika Translation Language Azure Cognitive Services Translate API The OpenMPF exposes data processing and job management web services via a User Interface (UI). These services allow users to upload media, create media processing jobs, determine the status of jobs, and retrieve the artifacts associated with completed jobs. The web services give application developers flexibility to use the OpenMPF in their preferred environment and programming language.",
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‎docs/site/sitemap.xml‎

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