Package: transforEmotion 0.1.7

transforEmotion: Sentiment Analysis for Text, Image and Video using Transformer Models

Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.

Authors:Alexander Christensen [aut], Hudson Golino [aut], Aleksandar Tomašević [aut, cre]

transforEmotion_0.1.7.tar.gz
transforEmotion_0.1.7.zip(r-4.7)transforEmotion_0.1.7.zip(r-4.6)transforEmotion_0.1.7.zip(r-4.5)
transforEmotion_0.1.7.tgz(r-4.6-any)transforEmotion_0.1.7.tgz(r-4.5-any)
transforEmotion_0.1.7.tar.gz(r-4.7-any)transforEmotion_0.1.7.tar.gz(r-4.6-any)
transforEmotion_0.1.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
transforEmotion/json (API)

# Install 'transforEmotion' in R:

install.packages('transforEmotion', repos = c('https://atomashevic.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/atomashevic/transforemotion/issues

Datasets:

emotions - Emotions Data
neo_ipip_extraversion - NEO-PI-R IPIP Extraversion Item Descriptions
stop_words - Stop Words from the _tm_ Package
tinytrolls - Russian Trolls Data - Small Version

On CRAN:

6.96 score 38 stars 20 scripts 716 downloads 40 exports 85 dependencies

Last updated from:92c89ab801. Checks:7 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	WARNING	171
source / vignettes	OK	257
linux-release-x86_64	WARNING	229
macos-release-arm64	WARNING	153
macos-oldrel-arm64	WARNING	212
windows-devel	WARNING	139
windows-release	WARNING	137
windows-oldrel	WARNING	152
wasm-release	OK	172

Exports:.init_builtin_models add_vision_model as_rag_table check_findingemo_quality delete_transformer dlo_dynamics download_findingemo_data emoxicon_scores evaluate_emotions get_vision_model_config image_scores image_scores_dir is_vision_model_registered list_vision_models load_findingemo_annotations map_discrete_to_vad map_to_emo8 nlp_scores parse_rag_json plot_sim_emotions prepare_findingemo_evaluation punctuate rag rag_sentemo register_retriever register_vision_model remove_vision_model sentence_similarity setup_gpu_modules setup_miniconda setup_modules setup_popular_models show_vision_models simulate_video te_cleanup_default_venv transformer_scores vad_scores validate_rag_json validate_rag_predictions video_scores

Dependencies:askpass base64enc bit bit64 bslib cachem cli clipr cpp11 crayon curl digest dplyr evaluate farver fastmap fontawesome fs gargle generics ggplot2 glue googledrive gtable here highr hms htmltools htmlwidgets httr isoband jquerylib jsonlite knitr labeling lattice lifecycle lsa LSAfun magrittr Matrix memoise mime openssl pbapply pillar pkgconfig plyr png prettyunits progress purrr R6 rappdirs RColorBrewer Rcpp RcppTOML readr remotes reshape2 reticulate rgl rlang rmarkdown rprojroot S7 sass scales SnowballC stringi stringr sys textdata tibble tidyselect tinytex tzdb utf8 uuid vctrs viridisLite vroom withr xfun yaml

Evaluating Emotion Classification with evaluate_emotions()

Rendered fromevaluate_emotions.Rmdusingknitr::rmarkdown

Last update: 2025-09-16
Started: 2025-09-16

Setup and Tutorial

1. Python setup using setup_miniconda() | 2. Using transformer_scores | 3. Using image_scores | 4. Using `video_scores'

Rendered fromSetup.Rmdusingknitr::rmarkdown

Last update: 2024-01-09
Started: 2022-04-13

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
transforEmotion-package	transforEmotion-package transforEmotion
Initialize Built-in Vision Models	.init_builtin_models
Vision Model Registry for transforEmotion Package	.vision_model_registry
User-Friendly Vision Model Management Functions	add_vision_model
Convert RAG JSON to a table	as_rag_table
Calculate the moving average for a time series	calculate_moving_average
Check FindingEmo Dataset Quality	check_findingemo_quality
Install Necessary Python Modules	check_nvidia_gpu
Delete a Transformer Model	delete_transformer
Dynamics function of the DLO model	dlo_dynamics
Download FindingEmo-Light Dataset	download_findingemo_data
Emotions Data	emotions
Emoxicon Scores	emoxicon_scores
Generate and emphasize sudden jumps in emotion scores	emphasize
Evaluate Emotion Classification Performance	evaluate_emotions
Generate observable emotion scores data from latent variables	generate_observables
Generate a matrix of Dynamic Error values for the DLO simulation	generate_q
Get Vision Model Configuration	get_vision_model_config
Calculate image scores using a Hugging Face CLIP model	image_scores
Calculate image scores for all images in a directory (fast batch)	image_scores_dir
Check if Vision Model is Registered	is_vision_model_registered
List Available Vision Models	list_vision_models
Load FindingEmo-Light Annotations	load_findingemo_annotations
Map Discrete Emotions to VAD (Valence-Arousal-Dominance) Framework	map_discrete_to_vad
Map FindingEmo Emotions to Emo8 Labels	map_to_emo8
Multivariate Normal (Gaussian) Distribution	MASS_mvrnorm
NEO-PI-R IPIP Extraversion Item Descriptions	neo_ipip_extraversion
Natural Language Processing Scores	nlp_scores
Parse RAG JSON	parse_rag_json
Plot the latent or the observable emotion scores.	plot_sim_emotions
Plot Evaluation Results	plot.emotion_evaluation
Prepare FindingEmo Data for Evaluation	prepare_findingemo_evaluation
Print method for emotion evaluation results	print.emotion_evaluation
Punctuation Removal for Text	punctuate
Retrieval-augmented Generation (RAG)	rag
RAG JSON utilities	rag_json_utils
Structured Emotion/Sentiment via RAG (Small LLMs)	rag_sentemo
Register a custom retriever	register_retriever
Register a Vision Model	register_vision_model
Remove a Vision Model	remove_vision_model
Sentiment Analysis Scores	sentence_similarity
Install GPU Python Modules	setup_gpu_modules
Deprecated: Miniconda setup (use uv instead)	setup_miniconda
Setup Required Python Modules	setup_modules
Quick Setup for Popular Models	setup_popular_models
Show Available Vision Models	show_vision_models
Simulate latent and observed emotion scores for a single "video"	simulate_video
Stop Words from the _tm_ Package	stop_words
Summary method for emotion evaluation results	summary.emotion_evaluation
Remove reticulate's default virtualenv (r-reticulate)	te_cleanup_default_venv
Russian Trolls Data - Small Version	tinytrolls
Sentiment Analysis Scores	transformer_scores
Direct VAD (Valence-Arousal-Dominance) Prediction	vad_scores
Validate a RAG JSON structure	validate_rag_json
Validate RAG Emotion/Sentiment Predictions	validate_rag_predictions
Run FER on a YouTube video using a Hugging Face CLIP model	video_scores