# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("Muqtadar08/skin_type_classifier")
model = AutoModelForImageClassification.from_pretrained("Muqtadar08/skin_type_classifier")Quick Links
Detects the skin type (dry, normal, oily) based on facial image.
See https://www.kaggle.com/code/dima806/skin-types-image-detection-vit for details.
Classification report:
precision recall f1-score support
dry 0.6471 0.5402 0.5888 224
normal 0.6031 0.7054 0.6502 224
oily 0.6054 0.6027 0.6040 224
accuracy 0.6161 672
macro avg 0.6185 0.6161 0.6143 672
weighted avg 0.6185 0.6161 0.6143 672
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Muqtadar08/skin_type_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")