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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()
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