| from resnet import get_model | |
| import torch | |
| from PIL import Image | |
| from torchvision.transforms.functional import pil_to_tensor | |
| model = get_model("r100", dropout=0.0, fp16=True, num_features=512).cuda() | |
| model.load_state_dict(torch.load("model.pt")) | |
| model.eval() | |
| img = pil_to_tensor(Image.open("test.jpg").resize((112,112))).permute(0, 1, 2).to("cuda", torch.float16).unsqueeze(dim = 0) | |
| embeddings = model(img) | |
| from insightface.app import FaceAnalysis | |
| import insightface | |
| from huggingface_hub import snapshot_download | |
| snapshot_download('Warlord-K/resnet100', local_dir='models/antelopev2') | |
| app = FaceAnalysis( | |
| name='antelopev2', root='.', providers=['CUDAExecutionProvider', 'CPUExecutionProvider'] | |
| ) | |
| app.prepare(ctx_id=0, det_size=(640, 640)) | |
| handler_ante = insightface.model_zoo.get_model('models/antelopev2/glintr100.onnx') | |
| handler_ante.prepare(ctx_id=0) |