Transformer Emotion Analysis for Text, Image, Video, and Speech

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Documentation for package ‘transforEmotion’ version 0.1.9

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

transforEmotion-package	transforEmotion-package
.init_builtin_models	Initialize Built-in Vision Models
.vision_model_registry	Vision Model Registry for transforEmotion Package
add_vision_model	User-Friendly Vision Model Management Functions
annotate_faces	Code faces in the browser
annotation_agreement	Agreement between coders
annotation_progress	Progress of a face annotation task
annotation_questions	Questions for a face annotation task
annotation_task	Set up a face annotation task
as_rag_table	Convert RAG JSON to a table
calculate_moving_average	Calculate the moving average for a time series
calibrate_scores	Calibrate frame scores for posterior_scores()
check_findingemo_quality	Check FindingEmo Dataset Quality
consensus_labels	One label per item from several coders
delete_transformer	Delete a Transformer Model
detect_faces	Detect faces in images or a video
dlo_dynamics	Dynamics function of the DLO model
download_findingemo_data	Download FindingEmo-Light Dataset
draw_faces	Draw detected faces
emotions	Emotions Data
emoxicon_scores	Emoxicon Scores
emphasize	Generate and emphasize sudden jumps in emotion scores
evaluate_emotions	Evaluate Emotion Classification Performance
face_scores	Score selected faces
generate_observables	Generate observable emotion scores data from latent variables
generate_q	Generate a matrix of Dynamic Error values for the DLO simulation
get_vision_model_config	Get Vision Model Configuration
image_scores	Calculate image scores using a Hugging Face CLIP model
image_scores_dir	Calculate image scores for all images in a directory (fast batch)
is_vision_model_registered	Check if Vision Model is Registered
list_vision_models	List Available Vision Models
load_findingemo_annotations	Load FindingEmo-Light Annotations
map_discrete_to_vad	Map Discrete Emotions to VAD (Valence-Arousal-Dominance) Framework
map_to_emo8	Map FindingEmo Emotions to Emo8 Labels
MASS_mvrnorm	Multivariate Normal (Gaussian) Distribution
neo_ipip_extraversion	NEO-PI-R IPIP Extraversion Item Descriptions
nlp_scores	Natural Language Processing Scores
parse_rag_json	Parse RAG JSON
plot.emotion_evaluation	Plot Evaluation Results
plot.te_faces	Draw detected faces
plot_sim_emotions	Plot the latent or the observable emotion scores.
posterior_scores	Posterior emotions from frame scores
prepare_findingemo_evaluation	Prepare FindingEmo Data for Evaluation
print.emotion_evaluation	Print method for emotion evaluation results
punctuate	Punctuation Removal for Text
python_requirements	Python Requirements for transforEmotion
rag	Retrieval-augmented Generation (RAG)
rag_json_utils	RAG JSON utilities
rag_sentemo	Structured Emotion/Sentiment via RAG (Small LLMs)
read_annotations	Read the answers of a face annotation task
read_face_selection	Read faces chosen in the browser
register_retriever	Register a custom retriever
register_vision_model	Register a Vision Model
remove_vision_model	Remove a Vision Model
select_faces	Select faces to analyse
sentence_similarity	Sentiment Analysis Scores
setup_cache	Use a Shared or Offline Cache
setup_gpu_modules	Install GPU Python Modules
setup_miniconda	Deprecated: Miniconda setup (use uv instead)
setup_modules	Setup Required Python Modules
setup_popular_models	Quick Setup for Popular Models
show_vision_models	Show Available Vision Models
simulate_video	Simulate latent and observed emotion scores for a single "video"
speech_scores	Speech Emotion Scores for Segments of an Audio or Video File
stop_words	Stop Words from the _tm_ Package
summary.emotion_evaluation	Summary method for emotion evaluation results
te_cleanup_default_venv	Remove reticulate's default virtualenv (r-reticulate)
tinytrolls	Russian Trolls Data - Small Version
transforEmotion	transforEmotion-package
transformer_scores	Sentiment Analysis Scores
vad_scores	Direct VAD (Valence-Arousal-Dominance) Prediction
validate_rag_json	Validate a RAG JSON structure
validate_rag_predictions	Validate RAG Emotion/Sentiment Predictions
video_scores	Run FER on a YouTube video using a Hugging Face CLIP model
view_faces	Look at detected faces in the browser, and choose faces to analyse