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I want to understand that “bagtricks_pca” and “occluded_reid” are trained according to the configured parameters, but they cannot reach the accuracy you posted. The results are still very different. I don’t know why this is.
the results:
“bagtricks_pca”:
+--------------+---------------------+---------------------+--------------------+--------------------+
| dataset | map | rank-1 | rank-5 | rank-10 |
+--------------+---------------------+---------------------+--------------------+--------------------+
| Market1501 | 0.17728540318946004 | 0.40498812351543945 | 0.5881828978622328 | 0.6591448931116389 |
| DukeMTMCreID | 0.6451677264561732 | 0.8074506283662477 | 0.9124775583482945 | 0.9340215439856373 |
+--------------+---------------------+---------------------+--------------------+--------------------+
I want to understand that “bagtricks_pca” and “occluded_reid” are trained according to the configured parameters, but they cannot reach the accuracy you posted. The results are still very different. I don’t know why this is.
the results:
“bagtricks_pca”:
+--------------+---------------------+---------------------+--------------------+--------------------+
| dataset | map | rank-1 | rank-5 | rank-10 |
+--------------+---------------------+---------------------+--------------------+--------------------+
| Market1501 | 0.17728540318946004 | 0.40498812351543945 | 0.5881828978622328 | 0.6591448931116389 |
| DukeMTMCreID | 0.6451677264561732 | 0.8074506283662477 | 0.9124775583482945 | 0.9340215439856373 |
+--------------+---------------------+---------------------+--------------------+--------------------+
“occluded_reid” with occludedreid_resnet50ibna_config
+--------------+--------------------+--------------------+--------------------+--------------------+
| dataset | map | rank-1 | rank-5 | rank-10 |
+--------------+--------------------+--------------------+--------------------+--------------------+
| OccludedReID | 0.5465391874335267 | 0.577 | 0.745 | 0.806 |
| PartialReID | 0.6881890106551225 | 0.7333333333333333 | 0.8566666666666667 | 0.9233333333333333 |
+--------------+--------------------+--------------------+--------------------+--------------------+
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