Download examples/sample_inference.py from henry000/YOLO: direct link, hf CLI and curl.
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https://huggingface.co/spaces/henry000/YOLO/resolve/main/examples/sample_inference.py
- Command line
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hf download hf://spaces/henry000/YOLO/examples/sample_inference.py
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curl -L -o sample_inference.py https://huggingface.co/spaces/henry000/YOLO/resolve/main/examples/sample_inference.py
1.13 kB
| import sys | |
| from pathlib import Path | |
| import hydra | |
| project_root = Path(__file__).resolve().parent.parent | |
| sys.path.append(str(project_root)) | |
| from yolo import ( | |
| Config, | |
| FastModelLoader, | |
| ModelTester, | |
| ProgressLogger, | |
| create_converter, | |
| create_dataloader, | |
| create_model, | |
| ) | |
| from yolo.utils.model_utils import get_device | |
| def main(cfg: Config): | |
| progress = ProgressLogger(cfg, exp_name=cfg.name) | |
| device, use_ddp = get_device(cfg.device) | |
| dataloader = create_dataloader(cfg.task.data, cfg.dataset, cfg.task.task, use_ddp) | |
| if getattr(cfg.task, "fast_inference", False): | |
| model = FastModelLoader(cfg).load_model(device) | |
| else: | |
| model = create_model(cfg.model, class_num=cfg.dataset.class_num, weight_path=cfg.weight) | |
| model = model.to(device) | |
| converter = create_converter(cfg.model.name, model, cfg.model.anchor, cfg.image_size, device) | |
| solver = ModelTester(cfg, model, converter, progress, device) | |
| progress.start() | |
| solver.solve(dataloader) | |
| if __name__ == "__main__": | |
| main() | |