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.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
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+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+*.mp3 filter=lfs diff=lfs merge=lfs -text
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+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+Maria[[:space:]]9[[:space:]]phrases/front/002_camA_S1_angry.MOV filter=lfs diff=lfs merge=lfs -text
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KYC verification dataset.csv

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+person_id,Name,side,emotion
+1,Maria,front,angry
+1,Maria,front,neutral
+1,Maria,front,sad
+1,Maria,left,angry
+1,Maria,left,neutral
+1,Maria,left,sad
+1,Maria,right,angry
+1,Maria,right,neutral
+1,Maria,right,sad
+2,Taras,front,angry
+2,Taras,front,neutral
+2,Taras,front,sad
+2,Taras,left,angry
+2,Taras,left,neutral
+2,Taras,left,sad
+2,Taras,right,angry
+2,Taras,right,neutral
+2,Taras,right,sad

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README.md

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+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- video-classification
+- video-text-to-text
+tags:
+- video
+- Facial Recognition
+- Computer Vision
+- Machine learning
+- Emotion Recognition
+size_categories:
+- 1K<n<10K
+---
+# Video Dataset of Various Emotions for Recognition Tasks
+
+Dataset comprises **1,000+** videos featuring **11** facial emotions and **15** inner emotions expressed by individuals from diverse backgrounds, including various races, genders, and ages. It is designed for **emotion recognition** research, focusing on **emotion detection** and emotion **classification** tasks.
+
+By utilizing this dataset, researchers can explore advanced **emotion analysis** techniques and develop robust recognition models that can accurately identify and classify **facial expressions** and **emotional categories**.  - **[Get the data](https://unidata.pro/datasets/ai-avatar/?utm_source=huggingface&utm_medium=referral&utm_campaign=video-emotion-recognition-dataset)**
+
+The dataset includes a wide range of emotional expressions, allowing for comprehensive studies in emotion predictions and expression recognition.
+
+# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/ai-avatar/?utm_source=huggingface&utm_medium=referral&utm_campaign=video-emotion-recognition-dataset) to discuss your requirements and pricing options.
+
+## Metadata for the dataset
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Faf0c2d80d660c8d38184a9ff28a094b3%2FFrame%201%20(6).png?generation=1741771741312300&alt=media)
+Variables in .csv files:
+- id: Unique identifier for each video
+- inner_emotion: The inner emotion expressed in the video
+- facial_emotion: The facial emotion displayed in the video
+- transcript: Text transcription of the video's content
+- video: Link to the original video
+- text: Link to the transcription
+
+The dataset contains videos that capture a variety of facial expressions and emotions, including both positive and negative emotions. Each video is annotated with detailed information about the emotions displayed, enabling researchers to conduct in-depth analyses and comparisons across different emotion categories.
+
+# Frequently Asked Questions
+
+## Who can benefit from this video emotion recognition dataset?
+
+The dataset is suitable for AI researchers, computer vision engineers, academic institutions, robotics developers, and companies building emotionally aware applications. It can be used for facial expression analysis, affective computing, AI avatar development, human-computer interaction, virtual assistants, and emotion-aware recommendation systems.
+
+## How was the dataset collected?
+
+The videos were collected through crowdsourcing using a standardized acquisition process designed to capture consistent facial recordings from multiple participants.
+
+# 🌐 [UniData](https://unidata.pro/datasets/ai-avatar/?utm_source=huggingface&utm_medium=referral&utm_campaign=video-emotion-recognition-dataset) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects

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