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Reproduce the results #110
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Ya, you are right on the results. The MODEL_PATH="./checkpoints/TT_r100_max_pool_E_prelu_dr04_lr_01_l2_5e4_adaface_emb512_sgd_m09_bs512_ms1m_64_only_margin_SG_scale_true_bias_false_random_100_basic_model_latest.h5"
DATASET_PATH="/datasets/ms1m-retinaface-t1"
python3 evals.py -m ${MODEL_PATH} -t ${DATASET_PATH}/lfw.bin ${DATASET_PATH}/cfp_fp.bin ${DATASET_PATH}/agedb_30.bin
# Evaluating lfw: 100%|███████████████████████████████████| 94/94 [00:47<00:00, 1.98it/s]
# >>>> lfw evaluation max accuracy: 0.998667, thresh: 0.240591, previous max accuracy: 0.000000
# >>>> Improved = 0.998667
# Evaluating cfp_fp: 100%|███████████████████████████████████| 110/110 [00:51<00:00, 2.15it/s]
# >>>> cfp_fp evaluation max accuracy: 0.992286, thresh: 0.181722, previous max accuracy: 0.000000
# >>>> Improved = 0.992286
# Evaluating agedb_30: 100%|███████████████████████████████████| 94/94 [00:43<00:00, 2.18it/s]
# >>>> agedb_30 evaluation max accuracy: 0.984333, thresh: 0.172596, previous max accuracy: 0.000000
# >>>> Improved = 0.984333
Maybe just a difference in image encoding qulity when saving those bin files. You may just pick a same one comparing their accuracies. |
I got it. Thank a lot 🙏 |
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Thank you for the work.

I want to know how to reproduce the result in this report
I was unable to achieve the provided performance on
LFW
data (lfw.bin
from InsightFace data zoo->MS1M-ArcFace)For example, with the following model:
I obtained the results as follow:

lfw evaluation max accuracy:
0.998333
. However, it should be0.998667
as in the report.Note that:
lfw.bin
(61.5 mb) provided in this repo release, the results will be the same as in the tablelfw.bin
(61.7 mb) provided in the InsightFace data zoo->MS1M-ArcFace, the result was lower as I mentioned before.So, what are the differences between your provided
lfw.bin
@leondgarse and the corresponding file in InsightFace data zoo->MS1M-ArcFace?Does it account for the difference when reproducing the results?
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