From eef3c58b5ec5c84d81340f1a124178d97a45eb3d Mon Sep 17 00:00:00 2001 From: unknown Date: Fri, 29 May 2020 11:47:13 +0800 Subject: [PATCH] modify --- model_zoo/deeplabv3/README.md | 64 +++++++++++++++++++++++++ model_zoo/deeplabv3/evaluation.py | 2 +- model_zoo/deeplabv3/readme.txt | 0 model_zoo/deeplabv3/scripts/run_eval.sh | 4 +- model_zoo/deeplabv3/train.py | 5 +- 5 files changed, 69 insertions(+), 6 deletions(-) create mode 100644 model_zoo/deeplabv3/README.md delete mode 100644 model_zoo/deeplabv3/readme.txt diff --git a/model_zoo/deeplabv3/README.md b/model_zoo/deeplabv3/README.md new file mode 100644 index 00000000000..977da7040a7 --- /dev/null +++ b/model_zoo/deeplabv3/README.md @@ -0,0 +1,64 @@ +Deeplab-V3 Example + +Description +This is an example of training DeepLabv3 with PASCAL VOC 2012 dataset in MindSpore. +Paper Rethinking Atrous Convolution for Semantic Image Segmentation +Liang-Chieh Chen, George Papandreou, Florian Schroff, Hartwig Adam + + +Requirements +Install MindSpore. +Download the VOC 2012 dataset for training. +For more information, please check the resources below： +MindSpore tutorials +MindSpore API + +Notes: If you are running a fine-tuning or evaluation task, prepare the corresponding checkpoint file. + + +Running the Example + +Training +Set options in config.py. +Run run_standalone_train.sh for non-distributed training. +sh scripts/run_standalone_train.sh DEVICE_ID EPOCH_SIZE DATA_DIR +Run run_distribute_train.sh for distributed training. +sh scripts/run_distribute_train.sh DEVICE_NUM EPOCH_SIZE DATA_DIR MINDSPORE_HCCL_CONFIG_PATH + +Evaluation +Set options in evaluation_config.py. Make sure the 'data_file' and 'finetune_ckpt' are set to your own path. +Run run_eval.sh for evaluation. +sh scripts/run_eval.sh DEVICE_ID DATA_DIR + +Options and Parameters +It contains of parameters of Deeplab-V3 model and options for training, which is set in file config.py. + +Options: +config.py: + learning_rate Learning rate, default is 0.0014. + weight_decay Weight decay, default is 5e-5. + momentum Momentum, default is 0.97. + crop_size Image crop size [height, width] during training, default is 513. + eval_scales The scales to resize images for evaluation, default is [0.5, 0.75, 1.0, 1.25, 1.5, 1.75]. + output_stride The ratio of input to output spatial resolution, default is 16. + ignore_label Ignore label value, default is 255. + seg_num_classes Number of semantic classes, including the background class (if exists). + foreground classes + 1 background class in the PASCAL VOC 2012 dataset, default is 21. + fine_tune_batch_norm Fine tune the batch norm parameters or not, default is False. + atrous_rates Atrous rates for atrous spatial pyramid pooling, default is None. + decoder_output_stride The ratio of input to output spatial resolution when employing decoder + to refine segmentation results, default is None. + image_pyramid Input scales for multi-scale feature extraction, default is None. + + + +Parameters: +Parameters for dataset and network: + distribute Run distribute, default is false. + epoch_size Epoch size, default is 6. + batch_size batch size of input dataset: N, default is 2. + data_url Train/Evaluation data url, required. + checkpoint_url Checkpoint path, default is None. + enable_save_ckpt Enable save checkpoint, default is true. + save_checkpoint_steps Save checkpoint steps, default is 1000. + save_checkpoint_num Save checkpoint numbers, default is 1. \ No newline at end of file diff --git a/model_zoo/deeplabv3/evaluation.py b/model_zoo/deeplabv3/evaluation.py index 2c034675875..09c9a2b6921 100644 --- a/model_zoo/deeplabv3/evaluation.py +++ b/model_zoo/deeplabv3/evaluation.py @@ -26,7 +26,7 @@ parser = argparse.ArgumentParser(description="Deeplabv3 evaluation") parser.add_argument('--epoch_size', type=int, default=2, help='Epoch size.') parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.") parser.add_argument('--batch_size', type=int, default=2, help='Batch size.') -parser.add_argument('--data_url', required=True, default=None, help='Train data url') +parser.add_argument('--data_url', required=True, default=None, help='Evaluation data url') parser.add_argument('--checkpoint_url', default=None, help='Checkpoint path') args_opt = parser.parse_args() diff --git a/model_zoo/deeplabv3/readme.txt b/model_zoo/deeplabv3/readme.txt deleted file mode 100644 index e69de29bb2d..00000000000 diff --git a/model_zoo/deeplabv3/scripts/run_eval.sh b/model_zoo/deeplabv3/scripts/run_eval.sh index 12505828c65..2470138c335 100644 --- a/model_zoo/deeplabv3/scripts/run_eval.sh +++ b/model_zoo/deeplabv3/scripts/run_eval.sh @@ -15,8 +15,8 @@ # ============================================================================ echo "==============================================================================================================" echo "Please run the scipt as: " -echo "bash run_eval.sh DEVICE_ID EPOCH_SIZE DATA_DIR" -echo "for example: bash run_eval.sh 0 /path/zh-wiki/ " +echo "bash run_eval.sh DEVICE_ID DATA_DIR" +echo "for example: bash run_eval.sh /path/zh-wiki/ " echo "==============================================================================================================" DEVICE_ID=$1 diff --git a/model_zoo/deeplabv3/train.py b/model_zoo/deeplabv3/train.py index 237d2f48000..a0f5b01d0d7 100644 --- a/model_zoo/deeplabv3/train.py +++ b/model_zoo/deeplabv3/train.py @@ -27,13 +27,12 @@ from src.config import config parser = argparse.ArgumentParser(description="Deeplabv3 training") parser.add_argument("--distribute", type=str, default="false", help="Run distribute, default is false.") -parser.add_argument('--epoch_size', type=int, default=2, help='Epoch size.') +parser.add_argument('--epoch_size', type=int, default=6, help='Epoch size.') parser.add_argument('--batch_size', type=int, default=2, help='Batch size.') parser.add_argument('--data_url', required=True, default=None, help='Train data url') parser.add_argument("--device_id", type=int, default=0, help="Device id, default is 0.") parser.add_argument('--checkpoint_url', default=None, help='Checkpoint path') parser.add_argument("--enable_save_ckpt", type=str, default="true", help="Enable save checkpoint, default is true.") -parser.add_argument('--max_checkpoint_num', type=int, default=5, help='Max checkpoint number.') parser.add_argument("--save_checkpoint_steps", type=int, default=1000, help="Save checkpoint steps, default is 1000.") parser.add_argument("--save_checkpoint_num", type=int, default=1, help="Save checkpoint numbers, default is 1.") args_opt = parser.parse_args() @@ -80,7 +79,7 @@ if __name__ == "__main__": keep_checkpoint_max=args_opt.save_checkpoint_num) ckpoint_cb = ModelCheckpoint(prefix='checkpoint_deeplabv3', config=config_ck) callback.append(ckpoint_cb) - net = deeplabv3_resnet50(config.seg_num_classes, [args_opt.batch_size, 3, args_opt.crop_size, args_opt.crop_size], + net = deeplabv3_resnet50(config.seg_num_classes, [args_opt.batch_size, 3, args_opt.crop_size, args_opt.crop_size], infer_scale_sizes=config.eval_scales, atrous_rates=config.atrous_rates, decoder_output_stride=config.decoder_output_stride, output_stride=config.output_stride, fine_tune_batch_norm=config.fine_tune_batch_norm, image_pyramid=config.image_pyramid)