diff --git a/docs/images/000000014439.jpg b/docs/images/000000014439.jpg new file mode 100644 index 0000000000000000000000000000000000000000..56a4f66768c439adf0fadbde7b150b520c6d09e3 Binary files /dev/null and b/docs/images/000000014439.jpg differ diff --git a/docs/images/road554.png b/docs/images/road554.png new file mode 100644 index 0000000000000000000000000000000000000000..1ecd45d9403897aa048417a9b69ad06e7ce41016 Binary files /dev/null and b/docs/images/road554.png differ diff --git a/docs/tutorials/QUICK_STARTED_cn.md b/docs/tutorials/QUICK_STARTED_cn.md index 7f9b42a7e2db16091d59f89e8fd88ac67e7c37f8..1e628bf722df9562340e2a1bcbdc8114c315ca68 100644 --- a/docs/tutorials/QUICK_STARTED_cn.md +++ b/docs/tutorials/QUICK_STARTED_cn.md @@ -25,7 +25,7 @@ python dataset/roadsign_voc/download_roadsign_voc.py ## 三、训练、评估、预测 ### 1、训练 ``` -# 边训练边测试 CPU需要约1小时(use_gpu=false),1080Ti GPU需要约5分钟。 +# 边训练边测试,GPU硬件下训练过程约在半小时内结束 # -c 参数表示指定使用哪个配置文件 # -o 参数表示指定配置文件中的全局变量(覆盖配置文件中的设置),这里设置使用gpu, # --eval 参数表示边训练边评估,会自动保存一个评估结果最好的名为best_model.pdmodel的模型 @@ -53,6 +53,8 @@ python -u tools/train.py -c configs/yolov3_mobilenet_v1_roadsign.yml \ visualdl --logdir vdl_dir/scalar/ --host --port ``` +![](../images/visualdl_roadsign.png) + ### 2、评估 ``` # 评估 默认使用训练过程中保存的best_model @@ -61,7 +63,6 @@ visualdl --logdir vdl_dir/scalar/ --host --port python tools/eval.py -c configs/yolov3_mobilenet_v1_roadsign.yml -o use_gpu=true ``` -![](../images/visualdl_roadsign.png) ### 3、预测 ```