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- from romatch.benchmarks import MegaDepthPoseEstimationBenchmark
- import numpy as np
- def test_mega1500(model, name):
- mega1500_benchmark = MegaDepthPoseEstimationBenchmark("data/megadepth")
- mega1500_results = mega1500_benchmark.benchmark(model, model_name=name)
- return mega1500_results
- if __name__ == "__main__":
- from romatch import roma_outdoor
- device = "cuda"
- model = roma_outdoor(device = device, coarse_res = 672, upsample_res = 1344, use_custom_corr=True)
- experiment_name = "roma_latest"
- results = test_mega1500(model, experiment_name)
- print(results)
- # gotten on 3.12 env with torch 2.8.0
- reference_scores = [0.6271474434923545, 0.7673889435429945, 0.8642099162282599] # slightly worse.
- # old_reference_scores = [0.6235757679569996, 0.7648007367330985, 0.8630483724961098]
- assert np.isclose(results["auc_5"], reference_scores[0], atol=3e-1 / 100)
- assert np.isclose(results["auc_10"], reference_scores[1], atol=2e-1 / 100)
- assert np.isclose(results["auc_20"], reference_scores[2], atol=1e-1 / 100)
-
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