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Processor Type | Processor Subtype | Processor Function | Processor Name |
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Task Pre-processing: These are processes that must be executed on the input data before they are sent to labelers. | |||
On Task Creation: These are processes that are executed as soon as the tasks are first created in Taskmonk. | |||
Named Entity Recognition: Seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. | |||
Text | |||
Phrase Extractor | |||
Field Dictionary Matcher | |||
Transcribe Speech | |||
Split Audio On Pause | |||
Split Audio In Separate Channels | |||
Image | |||
Pose Detector | |||
Keypoint Detector | |||
Others | |||
File Download | |||
TmAnnotations Data Converter | |||
Optical Character Recognition | |||
On Level Change: These are processes that are executed when a task moves from one level to another. For example, after the labeler labels or skips a task. | |||
Named Entity Recognition | |||
Text | |||
Image | |||
Others | |||
TmAnnotations Data Converter | |||
UI | No processor available here. | ||
On Task Allocation Format: These are processes that are executed when a task is allocated to a labeler. | |||
Image | |||
Text | Dictionary Matcher | ||
Task Post-processing | |||
On Task Completion: These are processes that are executed after a labeler completes a task. | |||
Others | |||
TmAnnotations Data Converter | |||
Output Format: These are processes that are executed after the task is complete, and before the task is uploaded to the destination. | |||
Others |
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Click to Select the Transliteration Provider.
Click to Select the field that contains the source text. This is the text that must be transliterated.
Click to Select the source language. This is the language of the source text.
Click to Select the source script to input text. This is the script in which the input text is written. Thus, for example, you could enter text in Hindi written in English script.
Click to Select the target script into which the input text will be converted.
Click to Select the field that must store the transliteration output.
Click Add to include this capability into your project.
Phrase Extractor
Use the Phrase Extractor tool to identify and extract phrases that have a strong meaning.
Click to Select the input field. This is the field that contains the untagged text.
Enter the Anchor Word that must be used to identify phrases. For example, Big Data.
Enter the Prefix Count to specify the number of words preceding the Anchor Word that may be a part of the phrase.
Enter the Suffix Count to specify the number of words following the Anchor Word that may be a part of the phrase.
Click POS to specify the part of speech that the phrase should be tagged with.
Click Extractor Code Language to specify the language in which the extractor code is provided.
Supported languages are:Python.
Java.
Enter the Extraction Code in the language specified.
Click Add to include this capability into your project.
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Click to Select the field that stores the URL to the input audio file.
Click to Select the provider of the audio transcription.
Click to Select the field that must store the extracted text results.
Click Add to include this capability into your project.
Split Audio On Pause
Use the Split Audio On Pause tool to automatically split input audio into multiple files on detecting a pause of a given duration.
Click to Select the field containing the input URL.
Click to Select the field to store the output after the audio is split.
Enter the Duration to split in seconds as the minimum duration of the pause at which the audio should be split.
Click Add to include this capability into your project.
Split Audio in Separate Channels
Use the Split Audio in Separate Channels tool to automatically split input audio into multiple files based on the number of channels present.
Click to Select the field containing the input audio URL.
Click to Select the field to store the output after the audio is split.
Click Add to include this capability into your project.
Video Type Convertor
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Use the Video type Convertor tool to convert video files of different formats into a format that Taskmonk uses.
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Use the Pose Detector to detect human beings in images and identify their poses.
Click to Select the input field that contains the image that must be processed.
Click to Select the field containing the annotations.
Click Add to include this capability into your project.
Keypoint Detector
Use the Keypoint Detector tool to detect keypoints or interest points in a person identified in an image or a video.
Click to Select the input field that contains the image or the video that must be processed.
Click to Select the annotation field to which the output must be saved.
Click to Select the Type of Detector that you wish to employ. These include:
18 point pose keypoints.
21 point hand keypoints.
68 point face keypoints.
468 point face mesh.
Enter the Detection FPS to be used for detection
Click Add to include this capability into your project.
Search LinkedIn
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Use the Search LinkedIn tool to automatically search LinkedIn for details associated with specific people and organizations.
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Click to Select the fields that you want to merge.
Click to Select the field into which the merged output must be stored.
Click Add to include this capability into your project.
File Download
Use the File Download tool to automatically download a file on task creation.
Click to Select the field with the URL of the file to be downloaded.
Click Add to include this capability into your project.
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Click to Select the code language that you want to use and enter the Code to be run in the field provided.
Click Add to include this capability into your project.
TmAnnotations Data Convertor
Use the TmAnnotations Data Convertor tool to convert annotation data generated by Taskmonk to the format required by your downstream application.
Click to Select the field containing the annotations to be converted.
Click to Select the field that has the input URL for which the annotations are generated.
Enter the Code to be run to generate the output annotation file,
Specify the folder name present in your bucket to which you want to upload the annotations.
Click to Select the field where the URL of the output file is to be saved.
Click Add to include this capability into your project.
Optical Character Recognition
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