| from config import model | |
| from mmcv.utils import Config | |
| from mmdet.models import build_detector | |
| import torch | |
| def main(): | |
| print(f"Model type: {model['type']}") | |
| detector = build_detector(model, train_cfg=model.get('train_cfg'), test_cfg=model.get('test_cfg')) | |
| detector.eval() | |
| print(detector) | |
| dummy_input = torch.randn(1, 3, 800, 1333) | |
| with torch.no_grad(): | |
| output = detector.forward_dummy(dummy_input) | |
| print("Forward output:", output) | |
| if __name__ == "__main__": | |
| main() | |