Cifar10 Resnet18 Classifier

--- license: apache-2.0 tags: - image-classification - pytorch - resnet - cifar10 datasets: - cifar10 metrics: - accuracy --- # CIFAR-10 Image Classifier (ResNet-18) Model klasifikasi gambar berbasis **ResNet-18** yang di-fine-tune pada dataset **CIFAR-10**. ## Kelas yang Didukung airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck ## Cara Penggunaan ```python import torch from torchvision import models, transforms from huggingface_hub import hf_hub_download from PIL import Image CLASSES = ("airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck") # Unduh model model_path = hf_hub_download(repo_id="rifda83/cifar10-resnet18-classifier", filename="best_model.pth") model = models.resnet18(weights=None) model.fc = torch.nn.Linear(model.fc.in_features, 10) model.load_state_dict(torch.load(model_path, map_location="cpu")) model.eval() transform = transforms.Compose([ transforms.Resize((32, 32)), transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)), ]) image = Image.open("your_image.jpg").convert("RGB") tensor = transform(image).unsqueeze(0) with torch.no_grad(): probs = torch.softmax(model(tensor), dim=1)[0] print(CLASSES[probs.argmax()], f"100.0%") ``` ## Performa Model | Split | Accuracy | |-------|----------| | Test | ~88% |

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