hilmiatha/resnet18-flower-classifier

metrics: - name: Accuracy type: Accuracy value: 0.8980

ResNet18 Flower Classifier

This model classifies images into one of five flower types.

Usage

from torchvision import transforms
from PIL import Image
import torch
from torchvision.models import resnet18

model = resnet18(weights=None)
model.load_state_dict(torch.load('path_to_model/pytorch_model.bin'))
model.eval()

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])
])

image = Image.open('path_to_image.jpg')
image = transform(image).unsqueeze(0)

with torch.no_grad():
    output = model(image)
    _, predicted = torch.max(output.data, 1)
    print(predicted.item())