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README.md

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 license: cc-by-nc-4.0
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-SAFFIRE (South Asian Facial Features in Real Environments) is a high-quality annotated facial dataset designed for age, gender, occlusion, and pose estimation. It comprises diverse South Asian faces captured in real-world conditions, ensuring variability in lighting, background, and expressions. The dataset includes detailed annotations for facial attributes, making it valuable for robust AI model training.
+SAFFIRE (South Asian Facial Features in Real Environments) is a high-quality annotated facial dataset designed for age, gender, occlusion, and pose estimation. It comprises diverse South Asian faces captured in real-world conditions, ensuring variability in lighting, background, and expressions. The dataset includes detailed annotations for facial attributes, making it valuable for robust AI model training.
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+For further information and citation please refer to the paper: SAFFIRE: South Asian Facial Features in Real Environments- a high-quality annotated facial dataset for Age, Gender, Occlusion, and Pose estimation
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+There are 2 files in the dataset: 1st PK-face.zip and 2nd Face-annotation.csv. The first file is a zipped compression of a folder containing actual facial images. While the later contains the details of annotation recorded for those facial images.
+The CSV file contains 6 columns details are as follows:
+ImageID: Unique ID of the image
+Path: Physical path of the image inside the uploaded folder
+Gender: Assigned gender to the facial image (Male or Female)
+Age-group: Assigned age group to the facial image (Juvenile: 0-18, Adult: 19-59, Senior: 60+)
+Pose: Assigned pose of the facial image (Frontal, Three-Quarter, Profile)
+Occlusive: Signifies whether the facial image is clear or occlusive in nature (Yes or No)