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--- |
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license: apache-2.0 |
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library_name: transformers |
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pipeline_tag: image-classification |
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--- |
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# body_complexion |
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This is a fine-tuned [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) model. Dataset with men of |
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different bode complexion was used for fine-tuning. |
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### Intended Use: |
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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: |
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- Health and fitness platforms for body type analysis |
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- Clothing recommendation systems tailored for different body types |
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- Visual content moderation systems to filter images based on body type |
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### Launch |
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```python |
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import torch |
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from PIL import Image |
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from transformers import ResNetForImageClassification, AutoImageProcessor |
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processor = AutoImageProcessor.from_pretrained('glazzova/body_complexion') |
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model = ResNetForImageClassification.from_pretrained('glazzova/body_complexion') |
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image = Image.open('your_pic.jpeg') |
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inputs = processor(image, return_tensors="pt") |
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with torch.no_grad(): |
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logits = model(**inputs).logits |
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# model predicts one of the 4 classes |
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predicted_label = logits.argmax(-1).item() |
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print(model.config.id2label[predicted_label]) |
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