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!19374 add gpu index in readme.txt of FaceQualityAssessment 

Merge pull request !19374 from 周莉莉/code_docs
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i-robot 2021-07-05 06:38:45 +00:00 committed by Gitee
parent 5a5b709cc5 656d6a6390
commit 49ea9546c0
2 changed files with 30 additions and 30 deletions
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52
model_zoo/research/cv/FaceQualityAssessment/README.md
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@ -442,35 +442,35 @@ sh run_export_cpu.sh [PRETRAINED_BACKBONE] [BATCH_SIZE] [FILE_NAME](optional)
### Training Performance
| Parameters | Ascend | CPU |
| -------------------------- | ------------------------------------------------- | ------------------------------------------ |
| Model Version | V1 | V1 |
| Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory 755G; OS Euler2.8 | Intel(R) Xeon(R) CPU E5-2690 v4 |
| Uploaded Date | 09/30/2020 (month/day/year) | 05/14/2021 (month/day/year) |
| MindSpore Version | 1.0.0 | 1.2.0 |
| Dataset | 122K images | 122K images |
| Training Parameters | epoch=40, batch_size=32, momentum=0.9, lr=0.02 | epoch=40, batch_size=32, momentum=0.9, lr=0.02 |
| Optimizer | Momentum | Momentum |
| Loss Function | MSELoss, Softmax Cross Entropy | MSELoss, Softmax Cross Entropy |
| Outputs | probability and point | probability and point |
| Speed | 1pc: 200-240 ms/step; 8pcs: 35-40 ms/step | 1pc: 6 s/step |
| Total time | 1ps: 2.5 hours; 8pcs: 0.5 hours | 1ps: 32 hours |
| Checkpoint for Fine tuning | 16M (.ckpt file) | 16M (.ckpt file) |
| Parameters | Ascend | CPU | GPU |
| -------------------------- | ---------------------------------------------------------- | -------------------------------------------- | -------------------------------------------- |
| Model Version | V1 | V1 | V1 |
| Resource | Ascend 910; CPU 2.60GHz, 192cores; Memory 755G; OS Euler2.8| Intel(R) Xeon(R) CPU E5-2690 v4 | NV SMX2 V100-32G |
| Uploaded Date | 09/30/2020 (month/day/year) | 05/14/2021 (month/day/year) | 07/06/2021 (month/day/year) |
| MindSpore Version | 1.0.0 | 1.2.0 | 1.3.0 |
| Dataset | 122K images | 122K images | 122K images |
| Training Parameters | epoch=40, batch_size=32, momentum=0.9, lr=0.02 | epoch=40, batch_size=32, momentum=0.9, lr=0.02| epoch=40, batch_size=32, momentum=0.9, lr=0.02|
| Optimizer | Momentum | Momentum | Momentum |
| Loss Function | MSELoss, Softmax Cross Entropy | MSELoss, Softmax Cross Entropy | MSELoss, Softmax Cross Entropy |
| Outputs | probability and point | probability and point | probability and point |
| Speed | 1pc: 200-240 ms/step; 8pcs: 35-40 ms/step | 1pc: 6 s/step | 1pc: 71ms/step, 8pcs: 40ms/step |
| Total time | 1ps: 2.5 hours; 8pcs: 0.5 hours | 1ps: 32 hours | 1ps: 0.5h, 8pcs: 0.25h |
| Checkpoint for Fine tuning | 16M (.ckpt file) | 16M (.ckpt file) |
### Evaluation Performance
| Parameters | Ascend | CPU |
| ------------------- | --------------------------- | --------------------------- |
| Model Version | V1 | V1 |
| Resource | Ascend 910; OS Euler2.8 | Intel(R) Xeon(R) CPU E5-2690 v4 |
| Uploaded Date | 09/30/2020 (month/day/year) | 05/14/2021 (month/day/year) |
| MindSpore Version | 1.0.0 | 1.2.0 |
| Dataset | 2K images | 2K images |
| batch_size | 256 | 256 |
| Outputs | IPN, MAE | IPN, MAE |
| Accuracy | 8 pcs: IPN of 5 keypoints:19.5 | 1 pcs: IPN of 5 keypoints:20.09 |
| | 8 pcs: MAE of elur:18.02 | 1 pcs: MAE of elur:18.23 |
| Model for inference | 16M (.ckpt file) | 16M (.ckpt file) |
| Parameters | Ascend | CPU | GPU |
| ------------------- | ----------------------------- | ------------------------------- | ------------------------------- |
| Model Version | V1 | V1 | V1 |
| Resource | Ascend 910; OS Euler2.8 | Intel(R) Xeon(R) CPU E5-2690 v4 | NV SMX2 V100-32G |
| Uploaded Date | 09/30/2020 (month/day/year) | 05/14/2021 (month/day/year) | 07/06/2021 (month/day/year) |
| MindSpore Version | 1.0.0 | 1.2.0 | 1.3.0 |
| Dataset | 2K images | 2K images | 2K images |
| batch_size | 256 | 256 | 256 |
| Outputs | IPN, MAE | IPN, MAE | IPN, MAE |
| Accuracy | 8 pcs: IPN of 5 keypoints:19.5| 1 pcs: IPN of 5 keypoints:20.09 | 8 pcs: IPN of 5 keypoints:19.29 |
| | 8 pcs: MAE of elur:18.02 | 1 pcs: MAE of elur:18.23 | 8 pcs: MAE of elur:18.04 |
| Model for inference | 16M (.ckpt file) | 16M (.ckpt file) | 16M (.ckpt file) |
# [ModelZoo Homepage](#contents)

8
model_zoo/research/cv/FaceQualityAssessment/default_config.yaml
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@ -8,7 +8,7 @@ checkpoint_url: ""
data_path: "/cache/data"
output_path: "/cache/train"
load_path: "/cache/checkpoint_path"
device_target: "Ascend"
device_target: "Ascend" # choices in ("Ascend", "CPU", "GPU")
need_modelarts_dataset_unzip: True
modelarts_dataset_unzip_name: "face_quality_dataset"
@ -32,7 +32,7 @@ weight_decay: 0.0005
momentum: 0.9
max_epoch: 40
warmup_epochs: 0
pretrained: ''
pretrained: '' # change to your own pretrained ckpt
# logging related
log_interval: 10
@ -41,10 +41,10 @@ ckpt_interval: 500
# train option
is_distributed: 0
train_label_file: ''
train_label_file: '' # change to your own train data path
# eval option
eval_dir: ''
eval_dir: '' # change to your own eval data path
# export option
batch_size: 8