import torch
from torchvision import transforms
from PIL import Image

# Load model (implement loading logic)
# model = load_model()

# Define transform
transform = transforms.Compose([
    transforms.Resize((224, 224)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])

# Inference
image = Image.open("path/to/image.jpg")
input_tensor = transform(image).unsqueeze(0)
with torch.no_grad():
    outputs = model(input_tensor)
    predicted_class = torch.argmax(outputs, dim=1)

kingkenche/stl10-resnet18

STL-10 ResNet-18 Classification Model

Model Details

Class Names

Usage

kingkenche/
stl10-resnet18