Fix seed and add statistics

2 years ago · e83cda7b46
parent 413d9a6606
commit e83cda7b46
21 changed files with 41 additions and 27 deletions
--- a/test_tipc/configs/cd/_base_/airchange.yaml
+++ b/test_tipc/configs/cd/_base_/airchange.yaml
@ -1,5 +1,7 @@
 # Basic configurations of AirChange dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: CDDataset
--- a/test_tipc/configs/cd/_base_/levircd.yaml
+++ b/test_tipc/configs/cd/_base_/levircd.yaml
@ -1,5 +1,7 @@
 # Basic configurations of LEVIR-CD dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: CDDataset
--- a/test_tipc/configs/clas/_base_/ucmerced.yaml
+++ b/test_tipc/configs/clas/_base_/ucmerced.yaml
@ -1,5 +1,7 @@
 # Basic configurations of UCMerced dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: ClasDataset
--- a/test_tipc/configs/clas/condensenetv2/train_infer_python.txt
+++ b/test_tipc/configs/clas/condensenetv2/train_infer_python.txt
@ -4,7 +4,7 @@ python:python
 gpu_list:0|0,1
 use_gpu:null|null
 --precision:null
--num_epochs:lite_train_lite_infer=3|lite_train_whole_infer=3|whole_train_whole_infer=10
+--num_epochs:lite_train_lite_infer=3|lite_train_whole_infer=3|whole_train_whole_infer=20
 --save_dir:adaptive
 --train_batch_size:lite_train_lite_infer=16|lite_train_whole_infer=16|whole_train_whole_infer=16
 --model_path:null
--- a/test_tipc/configs/det/_base_/rsod.yaml
+++ b/test_tipc/configs/det/_base_/rsod.yaml
@ -1,5 +1,7 @@
 # Basic configurations of RSOD dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: VOCDetDataset
--- a/test_tipc/configs/det/_base_/sarship.yaml
+++ b/test_tipc/configs/det/_base_/sarship.yaml
@ -1,5 +1,7 @@
 # Basic configurations of SARShip dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: VOCDetDataset
--- a/test_tipc/configs/res/_base_/rssr.yaml
+++ b/test_tipc/configs/res/_base_/rssr.yaml
@ -1,5 +1,7 @@
 # Basic configurations of RSSR dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: ResDataset
--- a/test_tipc/configs/seg/_base_/rsseg.yaml
+++ b/test_tipc/configs/seg/_base_/rsseg.yaml
@ -1,5 +1,7 @@
 # Basic configurations of RSSeg dataset

+seed: 1024
+
 datasets:
    train: !Node
        type: SegDataset
@ -32,8 +34,8 @@ transforms:
        - !Node
          type: Normalize
          args:
-            mean: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
-            std: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
+            mean: [0.5, 0.5, 0.5]
+            std: [0.5, 0.5, 0.5]
        - !Node
          type: ArrangeSegmenter
          args: ['train']
@ -47,8 +49,8 @@ transforms:
        - !Node
          type: Normalize
          args:
-            mean: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
-            std: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
+            mean: [0.5, 0.5, 0.5]
+            std: [0.5, 0.5, 0.5]
        - !Node
          type: ArrangeSegmenter
          args: ['eval']
--- a/test_tipc/configs/seg/bisenetv2/bisenetv2_rsseg.yaml
+++ b/test_tipc/configs/seg/bisenetv2/bisenetv2_rsseg.yaml
@ -5,7 +5,7 @@ _base_: ../_base_/rsseg.yaml
 save_dir: ./test_tipc/output/seg/bisenetv2/

 model: !Node
-    type: BiSeNet V2
+    type: BiSeNetV2
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/configs/seg/bisenetv2/train_infer_python.txt
+++ b/test_tipc/configs/seg/bisenetv2/train_infer_python.txt
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/deeplabv3p/deeplabv3p_rsseg.yaml
+++ b/test_tipc/configs/seg/deeplabv3p/deeplabv3p_rsseg.yaml
@ -7,5 +7,5 @@ save_dir: ./test_tipc/output/seg/deeplabv3p/
 model: !Node
    type: DeepLabV3P
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/configs/seg/deeplabv3p/train_infer_python.txt
+++ b/test_tipc/configs/seg/deeplabv3p/train_infer_python.txt
@ -4,7 +4,7 @@ python:python
 gpu_list:0|0,1
 use_gpu:null|null
 --precision:null
--num_epochs:lite_train_lite_infer=3|lite_train_whole_infer=3|whole_train_whole_infer=30
+--num_epochs:lite_train_lite_infer=3|lite_train_whole_infer=3|whole_train_whole_infer=20
 --save_dir:adaptive
 --train_batch_size:lite_train_lite_infer=4|lite_train_whole_infer=4|whole_train_whole_infer=4
 --model_path:null
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/farseg/farseg_rsseg.yaml
+++ b/test_tipc/configs/seg/farseg/farseg_rsseg.yaml
@ -7,5 +7,5 @@ save_dir: ./test_tipc/output/seg/farseg/
 model: !Node
    type: FarSeg
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/configs/seg/farseg/train_infer_python.txt
+++ b/test_tipc/configs/seg/farseg/train_infer_python.txt
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/fast_scnn/fast_scnn_rsseg.yaml
+++ b/test_tipc/configs/seg/fast_scnn/fast_scnn_rsseg.yaml
@ -5,7 +5,7 @@ _base_: ../_base_/rsseg.yaml
 save_dir: ./test_tipc/output/seg/fast_scnn/

 model: !Node
-    type: Fast-SCNN
+    type: FastSCNN
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/configs/seg/fast_scnn/train_infer_python.txt
+++ b/test_tipc/configs/seg/fast_scnn/train_infer_python.txt
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/hrnet/hrnet_rsseg.yaml
+++ b/test_tipc/configs/seg/hrnet/hrnet_rsseg.yaml
@ -7,5 +7,5 @@ save_dir: ./test_tipc/output/seg/hrnet/
 model: !Node
    type: HRNet
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/configs/seg/hrnet/train_infer_python.txt
+++ b/test_tipc/configs/seg/hrnet/train_infer_python.txt
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/unet/train_infer_python.txt
+++ b/test_tipc/configs/seg/unet/train_infer_python.txt
@ -27,7 +27,7 @@ null:null
 ===========================export_params===========================
 --save_dir:adaptive
 --model_dir:adaptive
--fixed_input_shape:[-1,10,512,512]
+--fixed_input_shape:[-1,3,512,512]
 norm_export:deploy/export/export_model.py
 quant_export:null
 fpgm_export:null
--- a/test_tipc/configs/seg/unet/unet_rsseg.yaml
+++ b/test_tipc/configs/seg/unet/unet_rsseg.yaml
@ -7,5 +7,5 @@ save_dir: ./test_tipc/output/seg/unet/
 model: !Node
    type: UNet
    args:
-        in_channels: 10
+        in_channels: 3
        num_classes: 5
--- a/test_tipc/docs/test_train_inference_python.md
+++ b/test_tipc/docs/test_train_inference_python.md
@ -19,7 +19,7 @@ Linux GPU/CPU 基础训练推理测试的主程序为`test_train_inference_pytho
 |  变化检测  | FC-Siam-conc | 正常训练 | 正常训练 | IoU=65.79% |
 |  变化检测  | FC-Siam-diff | 正常训练 | 正常训练 | IoU=61.23% |
 |  变化检测  | FCCDN | 正常训练 | 正常训练 | IoU=24.42% |
-|  场景分类  | CondenseNet V2 | 正常训练 | 正常训练 | Acc(top1)= |
+|  场景分类  | CondenseNet V2 | 正常训练 | 正常训练 | Acc(top1)=60.42% |
 |  场景分类  | HRNet | 正常训练 | 正常训练 | Acc(top1)=99.37% |
 |  场景分类  | MobileNetV3 | 正常训练 | 正常训练 | Acc(top1)=99.58% |
 |  场景分类  | ResNet50-vd | 正常训练 | 正常训练 | Acc(top1)=99.26% |
@ -31,12 +31,12 @@ Linux GPU/CPU 基础训练推理测试的主程序为`test_train_inference_pytho
 |  目标检测  | PP-YOLO Tiny | 正常训练 | 正常训练 | mAP=44.27% |
 |  目标检测  | PP-YOLOv2 | 正常训练 | 正常训练 | mAP=59.37% |
 |  目标检测  | YOLOv3 | 正常训练 | 正常训练 | mAP=47.33% |
-|  图像分割  | BiSeNet V2 | 正常训练 | 正常训练 | mIoU= |
-|  图像分割  | DeepLab V3+ | 正常训练 | 正常训练 | mIoU=56.05% |
-|  图像分割  | FarSeg | 正常训练 | 正常训练 | mIoU=49.58% |
-|  图像分割  | Fast-SCNN | 正常训练 | 正常训练 | mIoU= |
-|  图像分割  | HRNet | 正常训练 | 正常训练 | mIoU= |
-|  图像分割  | UNet | 正常训练 | 正常训练 | mIoU=55.50% |
+|  图像分割  | BiSeNet V2 | 正常训练 | 正常训练 | mIoU=70.20 |
+|  图像分割  | DeepLab V3+ | 正常训练 | 正常训练 | mIoU=64.59% |
+|  图像分割  | FarSeg | 正常训练 | 正常训练 | mIoU=50.45% |
+|  图像分割  | Fast-SCNN | 正常训练 | 正常训练 | mIoU=48.97% |
+|  图像分割  | HRNet | 正常训练 | 正常训练 | mIoU=33.49% |
+|  图像分割  | UNet | 正常训练 | 正常训练 | mIoU=72.64% |

 *注：参考预测精度为whole_train_whole_infer模式下单卡训练汇报的精度数据。*