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a/docs/assets/images/ocr/text_detection.png and b/docs/assets/images/ocr/text_detection.png differ diff --git a/docs/assets/images/ocr/with_regions.png b/docs/assets/images/ocr/with_regions.png index 887b36593f..f6de7310e7 100644 Binary files a/docs/assets/images/ocr/with_regions.png and b/docs/assets/images/ocr/with_regions.png differ diff --git a/docs/demos/diagnoses_procedures.md b/docs/demos/diagnoses_procedures.md index 94a013f76d..4be76e6c9f 100644 --- a/docs/demos/diagnoses_procedures.md +++ b/docs/demos/diagnoses_procedures.md @@ -58,7 +58,19 @@ data: url: https://demo.johnsnowlabs.com/healthcare/NER_CLINICAL_MULTI/ - text: Colab type: blue_btn - url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/healthcare/NER_CLINICAL_MULTI.ipynb + url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/healthcare/NER_CLINICAL_MULTI.ipynb + - title: Model Augmentation with LangTest + id: model_augmentation_langtest + image: + src: /assets/images/Model_Augmentation_with_LangTest.svg + excerpt: In this demo, We are showing the results of the Original Model on the original text and on the corruped text. In addition, We are showing the result of the Langtest model which is augmented with langtest library for corrupted text cases. + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/healthcare/LANGTEST_NER/ + - text: Colab + type: blue_btn + url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/healthcare/LANGTEST_NER.ipynb - title: Identify diagnosis and symptoms assertion status id: identify_diagnosis_and_symptoms_assertion_status image: diff --git a/docs/demos/extract_handwritten_texts.md b/docs/demos/extract_handwritten_texts.md index 56e2416042..c9738b8196 100644 --- a/docs/demos/extract_handwritten_texts.md +++ b/docs/demos/extract_handwritten_texts.md @@ -44,5 +44,17 @@ data: - text: Colab type: blue_btn url: https://colab.research.google.com/github/JohnSnowLabs/spark-ocr-workshop/blob/3.6.0/jupyter/SparkOcrImageHandwrittenDetection.ipynb + - title: Recognize Handwritten information in Document Images + id: recognize_handwritten_information_document_images + image: + src: /assets/images/Recognize_Handwritten_information_in_Document_Images.svg + excerpt: This demo recognizes handwritten information in documents using our pre-trained Spark OCR model. + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/ocr/RECOGNIZE_HANDWRITTEN/ + - text: Colab + type: blue_btn + url: https://github.com/JohnSnowLabs/spark-ocr-workshop/blob/master/jupyter/Cards/SparkOcrImageToTextHandwritten_V2_opt.ipynb --- diff --git a/docs/demos/extract_tables.md b/docs/demos/extract_tables.md index 10eca4a4db..86ac3e916a 100644 --- a/docs/demos/extract_tables.md +++ b/docs/demos/extract_tables.md @@ -57,4 +57,16 @@ data: - text: Colab type: blue_btn url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/ocr/PPTX_TABLE.ipynb + - title: Table and Form detection in Document Images + id: table_form_detection_document_images + image: + src: /assets/images/Table_and_Form_detection_in_Document_Images.svg + excerpt: This demo detects tables and forms in documents using our pre-trained Spark OCR model. + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/ocr/IMAGE_TABLE_FORM_DETECTION/ + - text: Colab + type: blue_btn + url: https://colab.research.google.com/github/JohnSnowLabs/spark-ocr-workshop/blob/master/jupyter/Cards/SparkOcrImageTableAndFormDetection.ipynb --- diff --git a/docs/demos/extract_text_from_documents.md b/docs/demos/extract_text_from_documents.md index 92067000db..196ec9f000 100644 --- a/docs/demos/extract_text_from_documents.md +++ b/docs/demos/extract_text_from_documents.md @@ -81,5 +81,16 @@ data: - text: Colab type: blue_btn url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/ocr/PPTX_TABLE.ipynb - ---- + - title: Detect Text in Document Images + id: detect_text_document_images + image: + src: /assets/images/Detect_Text_in_Document_Images.svg + excerpt: This demo detects text in documents using our pre-trained Spark OCR model. + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/ocr/TEXT_DETECTION_DIT/ + - text: Colab + type: blue_btn + url: https://github.com/JohnSnowLabs/spark-ocr-workshop/blob/master/jupyter/Cards/SparkOcrImageTextDetection.ipynb +--- \ No newline at end of file diff --git a/docs/demos/resolve_entities_codes.md b/docs/demos/resolve_entities_codes.md index 1a38c82bba..3ffd74d03e 100644 --- a/docs/demos/resolve_entities_codes.md +++ b/docs/demos/resolve_entities_codes.md @@ -178,4 +178,16 @@ data: - text: Colab type: blue_btn url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/healthcare/ER_CPT.ipynb + - title: Mapping ICD-10-CM Codes with Corresponding Medicare Severity-Diagnosis Related Group + id: mapping_codes_medicare_severity_diagnosis_related_group + image: + src: /assets/images/ICD-10-CMMS-DRG.svg + excerpt: This pretrained model maps ICD-10-CM codes with their corresponding Medicare Severity-Diagnosis Related Group (MS-DRG). + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/healthcare/ICD10CM_MS_DRG_MAPPER/ + - text: Colab + type: blue_btn + url: --- diff --git a/docs/demos/visual_document_understanding.md b/docs/demos/visual_document_understanding.md index 186b4974de..70e3261514 100644 --- a/docs/demos/visual_document_understanding.md +++ b/docs/demos/visual_document_understanding.md @@ -68,5 +68,17 @@ data: url: https://demo.johnsnowlabs.com/ocr/BRAND_EXTRACTION/ - text: Colab type: blue_btn - url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/ocr/BRAND_EXTRACTION.ipynb + url: https://colab.research.google.com/github/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/streamlit_notebooks/ocr/BRAND_EXTRACTION.ipynb + - title: Visual NER Key-Values v2 + id: visual_ner_key_values_v2 + image: + src: /assets/images/Visual_NER_Key-Values_v2.svg + excerpt: This demo extract the main document key points using our pre-trained Spark OCR model. + actions: + - text: Live Demo + type: normal + url: https://demo.johnsnowlabs.com/ocr/VISUAL_DOCUMENT_KEYVALUES_NER_LILT/ + - text: Colab + type: blue_btn + url: https://github.com/JohnSnowLabs/spark-ocr-workshop/blob/master/jupyter/SparkOCRVisualDocumentNer-FormParsing.ipynb --- diff --git a/docs/en/alab/annotation.md b/docs/en/alab/annotation.md index ab00fa06f6..1452c7b83e 100644 --- a/docs/en/alab/annotation.md +++ b/docs/en/alab/annotation.md @@ -112,7 +112,7 @@ To delete the label from the text, we first click on the text on the labeling ed When annotating text, it is possible and probable that the annotation is not very precise and the chunks contain leading/trailing spaces and punctuation marks. By default all the leading/trailing spaces and punctuation marks are excluded from the annotated chunk. The labeling editor settings has a new configuration option that can be used to enable/disable this feature if necessary. -![trim_spaces_punctuations](/assets/images/annotation_lab/4.1.0/trimming_characters.gif) +![trim_spaces_punctuations](/assets/images/annotation_lab/4.1.0/trimming_characters-min.gif)
@@ -128,7 +128,7 @@ To add an assertion label to an extracted entity, select the assertion label and Creating relations with the Annotation Lab is very simple. First, click on any one labeled entity, then press the r key and click on the second labeled entity. - + You can add a label to the relation, change its direction or delete it using the contextual menu displayed next to the relation arrow or from the relation box. @@ -140,7 +140,7 @@ You can add a label to the relation, change its direction or delete it using the From version 2.8.0, Annotation Lab supports cross-page NER annotation for Text projects. It means that Annotators can annotate a chunk starting at the bottom of one page and finishing on the next page. This feature is also available for Relations. Previously, relations were created between chunks located on the same page. But now, relations can be created among tokens located on different pages. The way to do this is to first [change the pagination settings](/docs/en/alab/import#dynamic-task-pagination) to include the tokens to be linked on the same page, then create the relation annotation between the tokens and finally go back to the original pagination settings. The annotation is presented through connectors after updating the pagination. - +
@@ -161,7 +161,7 @@ Here is how we can use it: The entire process is illustrated below: - + ### Support for multi-page PDF documents @@ -188,4 +188,4 @@ Just like for [Preannotation](/docs/en/alab/preannotation) servers, Annotation L To work on a Visual NER project, users have to deploy at least one OCR server. Any OCR server can perform preannotation. To select the OCR server, users need to go to the Import page, click on the OCR Server button on the top-right corner and from the popup, choose one of the available OCR servers. If no suitable OCR server is present, you can create a new server by selecting the `Create Server` option and then clicking on the `Deploy` button. - + diff --git a/docs/en/alab/annotation_configurations.md b/docs/en/alab/annotation_configurations.md index 1830d81d24..f727422274 100644 --- a/docs/en/alab/annotation_configurations.md +++ b/docs/en/alab/annotation_configurations.md @@ -40,7 +40,7 @@ This process is adapted for more complex workflows and large tasks. For simple p The Project Owner/Manager can activate this option from the Settings dialog (Customize Labels) in the Configuration step of the Setup page. Once enabled, annotators can see the submit button on the labeling page. A second option is available on the same dialog for Project Owner/Manager: _Serve next task after completion submission_. Once enabled, annotators can see the next task on the labeling page after submitting the completion for the current task. - + > **Note:** > @@ -53,7 +53,7 @@ The Project Owner/Manager can activate this option from the Settings di When predictions are available for a task, Annotator can accept the predictions with just one click and navigate automatically to the next task. When users click on Accept Prediction, a new completion is created based on the prediction, then submitted as ground truth, and the next task in line (assigned to the current annotator/reviewer and with Incomplete or In Progress status) is automatically served. - + > **NOTE:** Press backspace key (on windows) or delete key (on mac) to delete the selected relation from the labeling editor or use the delete action icon on the Relations widget. @@ -91,11 +91,11 @@ This option helps users quickly annotate sequences of the same label by keeping With the option unchecked: - + With the option checked: - +
@@ -103,7 +103,7 @@ With the option checked: This option keeps the annotated region selected after annotation. In this way, it will be easier for users to quickly change the assigned label for the last selected region if necessary. - +
@@ -119,7 +119,7 @@ This option adds line numbers to the text content to annotate in the labeling ed When checked, this option allow users to annotate all occurences of a text in the current task in one step. - + ## Labeling editor Customizations @@ -181,7 +181,7 @@ For obtaining the above display on a NER project, the config should look as foll Notice how users can search for the desired label using the filter bar: - +
@@ -229,19 +229,19 @@ Using the following Project Configuration we'll obtain the output illustrated below: - + ## Comments on the Labeling Page Since version 4.10.0, NLP Lab offers enhanced comment feature for labeling pages, enabling users to easily add, update, and delete comments within labeling pages. This feature enhances the communication between the annotators, improves work efficiency and enhances productivity. In order to use this feature, there is a New Burger menu at the top right corner of the labeling page. The dropdown through this menu allows users to add, update, and delete comments. -![Comments](/assets/images/annotation_lab/4.10.0/2.gif) +![Comments](/assets/images/annotation_lab/4.10.0/2-min.gif) ## Tags from the Labeling Screen From version 4.10 onwards, NLP Lab introduces an enhanced tags feature for labeling pages. This addition offers users a convenient method to create, attach, and delete tags directly on the labeling page. It greatly enhances organization and boosts productivity by streamlining task management, granting users greater flexibility in classifying and monitoring their labeled data. Similar to the aforementioned comment feature, this can also be accessed from the burger menu at the top right corner of the labeling page. From the dropdown, select "Assign Tags". -![tags](/assets/images/annotation_lab/4.10.0/3.gif) +![tags](/assets/images/annotation_lab/4.10.0/3-min.gif) Once the users select the tag/tags, they will be displayed against the tasks on the tasks page. @@ -249,7 +249,7 @@ Once the users select the tag/tags, they will be displayed against the tasks on Label configuration editor and Preview Window covers 50/50 part of the screen. It can make editing larger XML configurations difficult. For a better editing experience, we can use the Toggle Preview Window button to have the editor use full screen width. - + ## Switch Role