CLAMS App Directory
How to use CLAMS appsPermalink
- Want to know how to use CLAMS apps? Check out CLAMS App user manual.
- Want a human friendly views of MMIF JSON files? Visit MMIF visualizer repository.
App DirectoryPermalink
swt-detectionPermalink
Detects scenes with text, like slates, chyrons and credits.
llava-captionerPermalink
Applies llava to video frames.
whisper-wrapperPermalink
A CLAMS wrapper for Whisper-based ASR software originally developed by OpenAI.
distil-whisper-wrapperPermalink
The wrapper of Distil-Whisper, avaliable models: distil-large-v3, distil-large-v2, distil-medium.en, distil-small.en. The default model is distil-small.en.
simple-timepoints-stitcherPermalink
Stitches a sequence of TimePoint
annotations into a sequence of TimeFrame
annotations, performing simple smoothing of short peaks of positive labels.
tfidf-keywordextractorPermalink
extract keywords of a text document according to TF-IDF values. IDF values and all features come from related pickle files in the current directory.App can either take a simple text document or take a MMIF file generated from the text slicer app.
spacy-wrapperPermalink
Apply spaCy NLP to all text documents in a MMIF file.
text-slicerPermalink
Slice text snippets from a provided text document given time frames
east-textdetectionPermalink
OpenCV-based text localization app that used EAST text detection model. Please visit the source code repository for full documentation.
inaspeechsegmenter-wrapperPermalink
inaSpeechSegmenter is a CNN-based audio segmentation toolkit. The original software can be found at https://github.com/ina-foss/inaSpeechSegmenter .
doctr-wrapperPermalink
CLAMS app wraps the docTR, End-to-End OCR model, available at https://pypi.org/project/python-doctr . The model is capable of detecting text regions in the input image and recognizing text in the regions. The text-localized regions are organized hierarchically by the model into “pages” > “blocks” > “lines” > “words”, and this CLAMS app translates them into TextDocument
, Paragraphs
, Sentence
, and Token
annotations to represent recognized text contents, then aligns them to BoundingBox
annotations that represent the detected geometries. This hierarchical structure is also represented in the TextDocument
annotation output as two newlines (\n\n
) between “paragraphs”, one newline (\n
) between the “lines”, and one space (“ “) between the “words”. For the text recognition, the model is internally configured to use the “parseq” recognition model, and only works with English text at the moment.
pyscenedetect-wrapperPermalink
easyocr-wrapperPermalink
Using EasyOCR to extract text from timeframes
dbpedia-spotlight-wrapperPermalink
Apply named entity linking to all text documents in a MMIF file.
slatedetectionPermalink
This tool detects slates.
fewshotclassifierPermalink
This tool uses a vision model to classify video segments. Currenly supports “chyron” frame type.
barsdetectionPermalink
This tool detects SMPTE color bars.
parseqocr-wrapperPermalink
This tool applies Parseq OCR to a video or image and generates text boxes and OCR results.
tesseractocr-wrapperPermalink
This tool applies Tesseract OCR to a video or image and generates text boxes and OCR results.
chyron-detectionPermalink
This tool detects chyrons, generates time segments.
gentle-forced-aligner-wrapperPermalink
This CLAMS app aligns transcript and audio track using Gentle. Gentle is a robust yet lenient forced aligner built on Kaldi.This app only works when Gentle is already installed locally.Unfortunately, Gentle is not distributed as a Python package distribution.To get Gentle installation instruction, see https://lowerquality.com/gentle/ Make sure install Gentle from the git commit specified in analyzer_version
in this metadata.
tonedetectionPermalink
Detects spans of monotonic audio within an audio file
brandeis-acs-wrapperPermalink
Brandeis Acoustic Classification & Segmentation (ACS) is a audio segmentation tool developed at Brandeis Lab for Linguistics and Computation. The original software can be found at https://github.com/brandeis-llc/acoustic-classification-segmentation .
aapb-pua-kaldi-wrapperPermalink
A CLAMS wrapper for Kaldi-based ASR software originally developed by PopUpArchive and hipstas, and later updated by Kyeongmin Rim at Brandeis University. Wrapped software can be found at https://github.com/brandeis-llc/aapb-pua-kaldi-docker .