Datasets:
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README.md
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language:
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- en
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dataset_info:
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features:
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- name: image
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num_examples: 20
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download_size: 44094250
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dataset_size: 44991960
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---
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# Face segmentation
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An example of a dataset that we've collected for a photo edit App. The dataset includes 20 selfies of people (man and women) in segmentation masks and their visualisations.
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# File with the extension .csv
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includes the following information for each media file:
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**How it works**: *go to the "masks" folder and make sure that the file "1.png" is a segmentation mask of the selfi, created for the photo "1.png" in the "images" folder.*
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### This is just an example of the data
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Leave a request on [**https://trainingdata.pro/datasets**](https://trainingdata.pro/datasets/face-parsing?utm_source=huggingface&utm_medium=cpc&utm_campaign=face_segmentation) to discuss your requirements, learn about the price and buy the dataset.
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## [TrainingData](https://trainingdata.pro/datasets/face-parsing?utm_source=huggingface&utm_medium=cpc&utm_campaign=face_segmentation) provides high-quality data annotation tailored to your needs
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TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**
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*keywords: head segmentation dataset, face-generation, semantic segmentation, face parts recognition, human faces, portrait segmentation, human face extraction, image segmentation, annotation, biometric dataset, biometric data dataset, face recognition database, facial recognition, face forgery detection, face shape, facial gestures, ar, augmented reality, face recognition dataset, face detection dataset, facial analysis, human images dataset*
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language:
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- en
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tags:
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- ibeta
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- replay attack
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- video
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- liveness detection
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- biometric
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- anti-spoofing
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dataset_info:
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features:
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- name: image
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num_examples: 20
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download_size: 44094250
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dataset_size: 44991960
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size_categories:
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- 10K<n<100K
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---
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# Face segmentation
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An example of a dataset that we've collected for a photo edit App. The dataset includes 20 selfies of people (man and women) in segmentation masks and their visualisations.
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# The dataset is created on the basis of [iBeta Level 1 Dataset](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=face_segmentation)
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# File with the extension .csv
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includes the following information for each media file:
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**How it works**: *go to the "masks" folder and make sure that the file "1.png" is a segmentation mask of the selfi, created for the photo "1.png" in the "images" folder.*
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## 👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 25,000+ human images & videos - [Full dataset](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=face_segmentation)
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#**🚀 You can learn more about our high-quality unique datasets [here](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=face_segmentation)**
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*keywords: head segmentation dataset, face-generation, semantic segmentation, face parts recognition, human faces, portrait segmentation, human face extraction, image segmentation, annotation, biometric dataset, biometric data dataset, face recognition database, facial recognition, face forgery detection, face shape, facial gestures, ar, augmented reality, face recognition dataset, face detection dataset, facial analysis, human images dataset*
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