DeiT-Classification-Apparel 🏷️👕

A Deep Learning Model for Apparel Image Classification using DeiT

📝 Model Overview

The DeiT-Classification-Apparel model is a Vision Transformer (DeiT) trained to classify different types of apparel. It leverages Data-efficient Image Transformers (DeiT) for improved image recognition with minimal computational resources.

• Architecture: Vision Transformer (DeiT)
• Use Case: Apparel classification
• Framework: PyTorch
• Model Size: 343MB
• Files:
  • DeiT_Model_Parameter.pth – Trained model weights
  • label_encoder.pkl – Label encoder for class mapping

📂 Files and Usage

1️⃣ Load the Model

import torch
from torchvision import transforms
from PIL import Image
import pickle

# Load Model
model = torch.load_state_dict(torch.load("DeiT_Model_Parameter.pth", map_location=device))
model.eval()

# Load Label Encoder
with open("label_encoder.pkl", "rb") as f:
    label_encoder = pickle.load(f)

2️⃣ Perform Inference

def predict(image_path):
    # Load and preprocess image
    image = Image.open(image_path).convert("RGB")
    transform = transforms.Compose([
        transforms.Resize((224, 224)),
        transforms.ToTensor(),
    ])
    input_tensor = transform(image).unsqueeze(0)

    # Make prediction
    with torch.no_grad():
        output = model(input_tensor)
        predicted_label = output.argmax(1).item()
    
    return label_encoder.inverse_transform([predicted_label])[0]

# Example Usage
image_path = "sample.jpg"
prediction = predict(image_path)
print(f"Predicted Apparel: {prediction}")

📌 Applications

✅ Fashion e-commerce product categorization
✅ Retail inventory management
✅ Virtual try-on solutions
✅ Automated fashion recommendation

🛠️ Training Details

• Dataset: Custom apparel dataset
• Optimizer: Adam
• Loss Function: CrossEntropyLoss
• Hardware Used: NVIDIA T4 GPU

📢 Citation

If you use this model, please cite:

@misc{bobs24_deit_classification_2024,
  author = {bobs24},
  title = {DeiT-Classification-Apparel},
  year = {2024},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/bobs24/DeiT-Classification-Apparel}}
}