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

model = torchvision.models.resnet50(pretrained=False)
model.fc = torch.nn.Linear(in_features=2048, out_features=1)
model.load_state_dict(torch.load('/content/zero_shot_classification_model.pth'))
model.eval()

test_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])
])

test_image_path = '/content/test_img.png'  # Replace with your own test image path!
test_image = Image.open(test_image_path).convert('RGB')
test_image = test_transform(test_image)
test_image = test_image.unsqueeze(0)

with torch.no_grad():
    prediction = model(test_image)

probability = torch.sigmoid(prediction).item()

print(f"The probability of the image being a Roblox character is: {probability*100}%")