| import torch |
| from torchvision import transforms |
| from PIL import Image |
| from huggingface_hub import hf_hub_download |
|
|
| |
| repo_id = "USERNAME_ANDA/GeoX-Custom-Model" |
| path = hf_hub_download(repo_id=repo_id, filename="pytorch_model.bin") |
|
|
| |
| model = GeoXModel() |
| model.load_state_dict(torch.load(path)) |
| model.eval() |
|
|
| |
| def predict(img_path): |
| img = Image.open(img_path).convert('RGB') |
| preprocess = transforms.Compose([transforms.Resize(224), transforms.ToTensor()]) |
| img_t = preprocess(img).unsqueeze(0) |
| |
| with torch.no_grad(): |
| out = model(img_t) |
| print(f"Hasil Prediksi Koordinat: {out.numpy()}") |
|
|
| predict("test_foto.jpg") |