diff --git a/README.md b/README.md index 733007e..9c895d8 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@

-This warehouse has attempted to train two model architectures in total. The first one is to train and validate the `WIDERFACE` dataset using only the `yolov5/yolov8/yolo11` detection model architecture. +This warehouse has attempted to train two model architectures in total. The first one is to train and validate the `WIDERFACE` dataset using only the `yolov5/yolov8/yolo11 detection model` architecture. | | ARCH | GFLOPs | Easy | Medium | Hard | |:---------------------:|:------------:|:------:|:-----:|:------:|:-----:| @@ -47,10 +47,10 @@ The second method uses `Ultralytics' pose model` for joint training of faces and - [News🚀](#news) - [Background🏷](#background) - [Installation](#installation) -- [Usage](#usage) - - [Train](#train) - - [Eval](#eval) - - [Predict](#predict) +- [Usage✨](#usage) + - [Train⭐](#train) + - [Eval⭐](#eval) + - [Predict⭐](#predict) - [Maintainers🔥](#maintainers) - [Thanks♥️](#thanks️) - [Contributing🌞](#contributing) @@ -75,15 +75,15 @@ Note: the latest implementation of `YOLO11Face` in our warehouse is entirely bas See [INSTALL.md](./yolo8face/docs/INSTALL.md) -## Usage +## Usage✨ -### Train +### Train⭐ ```shell $ python3 pose_train.py --model yolo11s-pose.pt --data ./yolo11face/cfg/datasets/widerface-landmarks.yaml --epochs 300 --imgsz 800 --batch 8 --device 0 ``` -### Eval +### Eval⭐ ```shell # python pose_widerface.py --model yolo11s-pose_widerface.pt --source ../datasets/widerface/images/val/ --folder_pict ../datasets/widerface/wider_face_split/wider_face_val_bbx_gt.txt --save_txt true --imgsz 640 --conf 0.001 --iou 0.6 --max_det 1000 --batch 1 --device 7 @@ -111,7 +111,7 @@ Hard Val AP: 0.8523522955677869 ================================================= ``` -### Predict +### Predict⭐ ```shell # python3 pose_predict.py --model yolo11s-pose_widerface.pt --source ./yolo11face/assets/widerface_val/ --imgsz 640 --device 0