wukesong
5 years ago
2 changed files with 14 additions and 16 deletions
Split View
Diff Options
+ 1
- 1
model_zoo/official/cv/MCNN/README.md
View File
| @@ -102,7 +102,7 @@ sh run_standalone_eval_ascend.sh [DATA_PATH] [CKPT_NAME] | |||
| ## [Script Parameters](#contents) | |||
| ```python # 介绍主要参数 | |||
| ```python # parameters | |||
| Major parameters in train.py and config.py as follows: | |||
| --data_path: The absolute full path to the train and evaluation datasets. | |||
+ 13
- 15
model_zoo/research/cv/SE-Net/README.md
View File
| @@ -111,7 +111,7 @@ python eval.py --net=se-resnet50 --dataset=imagenet2012 --checkpoint_path=[CHECK | |||
| Parameters for both training and evaluation can be set in config.py. | |||
| - Config for SE-ResNet50, ImageNet2012 dataset | |||
| - Config for SE-Net, ImageNet2012 dataset | |||
| ```bash | |||
| "class_num": 1001, # dataset class number | |||
| @@ -159,7 +159,7 @@ Training result will be stored in the example path, whose folder name begins wit | |||
| ### Result | |||
| - Training SE-ResNet50 with ImageNet2012 dataset | |||
| - Training SE-Net with ImageNet2012 dataset | |||
| ```bash | |||
| # distribute training result(8 pcs) | |||
| @@ -189,7 +189,7 @@ bash run_eval.sh /imagenet/val/ /path/to/resnet-90_625.ckpt | |||
| ### Result | |||
| - Evaluating SE-ResNet50 with ImageNet2012 dataset | |||
| - Evaluating SE-Net with ImageNet2012 dataset | |||
| ```bash | |||
| result: {'top_5_accuracy': 0.9385269007731959, 'top_1_accuracy': 0.7774645618556701} | |||
| @@ -201,40 +201,38 @@ result: {'top_5_accuracy': 0.9385269007731959, 'top_1_accuracy': 0.7774645618556 | |||
| ### Evaluation Performance | |||
| #### SE-ResNet50 on ImageNet2012 | |||
| #### SE-Net on ImageNet2012 | |||
| | Parameters | Ascend 910 | |||
| | -------------------------- | ------------------------------------------------------------------------ | | |||
| | Model Version | SE-ResNet50 | | |||
| | Model Version | SE-Net | | |||
| | Resource | Ascend 910，CPU 2.60GHz 192cores，Memory 755G | | |||
| | uploaded Date | 03/19/2021 (month/day/year) | | |||
| | MindSpore Version | 0.7.0-alpha | | |||
| | MindSpore Version | 1.1.0 | | |||
| | Dataset | ImageNet2012 | | |||
| | Training Parameters | epoch=90, steps per epoch=5004, batch_size = 256 | | |||
| | Optimizer | Momentum | | |||
| | Loss Function | Softmax Cross Entropy | | |||
| | outputs | probability | | |||
| | Loss | 1.5931969 | | |||
| | Speed | # ms/step（8pcs） | | |||
| | Total time | # mins | | |||
| | Parameters (M) | 285M | | |||
| | Checkpoint for Fine tuning | # M (.ckpt file) | | |||
| | Scripts | [Link](XXXXXXXhttps://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/resnet) | | |||
| | Speed | 330.012 ms/step（8pcs） | | |||
| | Total time | 155 mins | | |||
| | Checkpoint for Fine tuning | 285M (.ckpt file) | | |||
| | Scripts | [Link](https://gitee.com/mindspore/mindspore/tree/r1.1/model_zoo/research/cv/SE-Net) | | |||
| ### Inference Performance | |||
| #### SE-ResNet50 on ImageNet2012 | |||
| #### SE-Net on ImageNet2012 | |||
| | Parameters | Ascend | | |||
| | ------------------- | --------------------------- | | |||
| | Model Version | SE-ResNet50 | | |||
| | Model Version | SE-Net | | |||
| | Resource | Ascend 910 | | |||
| | Uploaded Date | 03/19/2021 (month/day/year) | | |||
| | MindSpore Version | 0.7.0-alpha | | |||
| | MindSpore Version | 1.1.0 | | |||
| | Dataset | ImageNet2012 | | |||
| | batch_size | 256 | | |||
| | Accuracy | 77.74% | | |||
| | Model for inference | # (.air file) | | |||
| # [Description of Random Situation](#contents) | |||