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Zahaab/food-classifier
food-classifier is a image classification model from Zahaab. Use it when you need a label for an image. The card lists the license as mit.
This repository contains a pre-trained PyTorch model for classifying food based on images. The model file foodmodel.pth can be downloaded and used to classify images of pizza, steak or sushi.
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Updated Nov 11, 2024
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.pth16.3 MB · 100%
From the Hugging Face model README
This repository contains a pre-trained PyTorch model for classifying food based on images. The model file food_model.pth can be downloaded and used to classify images of pizza, steak or sushi.
The food_model.pth file is a PyTorch model trained on a dataset of food images. It achieves a test accuracy of 84.56%, making it a reliable choice for identifying pizza, steak, and sushi. The model is designed to be lightweight and efficient for real-time applications.
git clone <repository-url>
cd <repository-folder>
pip install torch torchvision
import torch
from torchvision import transforms
from PIL import Image
# Load the model
model = torch.load('aircraft_classifier.pth')
model.eval() # Set to evaluation mode
# Load and preprocess the image
transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor(),
])
img = Image.open('path_to_image.jpg')
img = transform(img).view(1, 3, 224, 224) # Reshape to (1, 3, 224, 224) for batch processing
# Predict
with torch.no_grad():
output = model(img)
_, predicted = torch.max(output, 1)
print("Predicted Food Type:", predicted.item())