body_complexion
This is a fine-tuned microsoft/resnet-50 model. Dataset with men of different bode complexion was used for fine-tuning.
Intended Use:
The model is intended for image classification tasks specifically related to men's body types. It is designed to classify images into four categories based on body complexion: skinny, ordinary, overweight, and very muscular. The model can be utilized in applications such as:
- Health and fitness platforms for body type analysis
- Clothing recommendation systems tailored for different body types
- Visual content moderation systems to filter images based on body type
Launch
import torch
from PIL import Image
from transformers import ResNetForImageClassification, AutoImageProcessor
processor = AutoImageProcessor.from_pretrained('glazzova/body_complexion')
model = ResNetForImageClassification.from_pretrained('glazzova/body_complexion')
image = Image.open('your_pic.jpeg')
inputs = processor(image, return_tensors="pt")
with torch.no_grad():
logits = model(**inputs).logits
# model predicts one of the 4 classes
predicted_label = logits.argmax(-1).item()
print(model.config.id2label[predicted_label])
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