- pytorch>=1.0
- loguru
NUS-WIDE-Split-txt Password: xrqd
usage: run.py [-h] [--dataset DATASET] [--root ROOT] [--batch-size BATCH_SIZE]
[--lr LR] [--code-length CODE_LENGTH] [--max-iter MAX_ITER]
[--max-epoch MAX_EPOCH] [--num-seen NUM_SEEN]
[--num-samples NUM_SAMPLES] [--num-workers NUM_WORKERS]
[--topk TOPK] [--gpu GPU] [--gamma GAMMA] [--mu MU]
DIHN_PyTorch
optional arguments:
-h, --help show this help message and exit
--dataset DATASET Dataset name.
--root ROOT Path of dataset
--batch-size BATCH_SIZE
Batch size.(default: 64)
--lr LR Learning rate.(default: 1e-4)
--code-length CODE_LENGTH
Binary hash code length.(default: 12)
--max-iter MAX_ITER Number of iterations.(default: 50)
--max-epoch MAX_EPOCH
Number of epochs.(default: 3)
--num-seen NUM_SEEN Number of unseen classes.(default: 7)
--num-samples NUM_SAMPLES
Number of sampling data points.(default: 2000)
--num-workers NUM_WORKERS
Number of loading data threads.(default: 0)
--topk TOPK Calculate map of top k.(default: all)
--gpu GPU Using gpu.(default: False)
--gamma GAMMA Hyper-parameter.(default: 200)
--mu MU Hyper-parameter.(default: 50)
cifar-10: 7 original classes, 3 incremental classes.
nus-wide: 11 original classes, 10 incremental classes.
| 12 bits | 24 bits | 32 bits | 48 bits | |
|---|---|---|---|---|
| ADSH cifar-10 MAP@ALL | 0.6433 | 0.6434 | 0.6451 | 0.6424 |
| +DIHN cifar-10 MAP@ALL | 0.9091 | 0.9117 | 0.9177 | 0.9217 |
| ADSH nus-wide-tc21 MAP@5000 | 0.8056 | 0.8551 | 0.8594 | 0.8625 |
| +DIHN nus-wide-tc21 MAP@5000 | 0.8361 | 0.9065 | 0.9028 | 0.9116 |