diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml
index 663cab5..a196e12 100644
--- a/.github/workflows/pylint.yml
+++ b/.github/workflows/pylint.yml
@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
diff --git a/README.md b/README.md
index db804c3..3b24908 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,5 @@
 # Labelme2YOLO
 
-**Forked from [rooneysh/Labelme2YOLO](https://github.com/rooneysh/Labelme2YOLO)**
-
 [![PyPI - Version](https://img.shields.io/pypi/v/labelme2yolo.svg)](https://pypi.org/project/labelme2yolo)
 ![PyPI - Downloads](https://img.shields.io/pypi/dm/labelme2yolo?style=flat)
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/labelme2yolo.svg)](https://pypi.org/project/labelme2yolo)
@@ -11,7 +9,7 @@ Labelme2YOLO is a powerful tool for converting LabelMe's JSON format to [YOLOv5]
 
 ## New Features
 
-* export data as yolo polygon annotation (for YOLOv5 v7.0 segmentation)
+* export data as yolo polygon annotation (for YOLOv5 & YOLOV8 segmentation)
 * Now you can choose the output format of the label text. The two available alternatives are `polygon` and bounding box (`bbox`).
 
 ## Installation
@@ -26,7 +24,7 @@ pip install labelme2yolo
 
 **--val\_size (Optional)** Validation dataset size, for example 0.2 means 20% for validation.
 
-**--test\_size (Optional)** Test dataset size, for example 0.2 means 20% for Test.
+**--test\_size (Optional)** Test dataset size, for example 0.1 means 10% for Test.
 
 **--json\_name (Optional)** Convert single LabelMe JSON file.
 
@@ -36,7 +34,25 @@ pip install labelme2yolo
 
 ## How to Use
 
-### 1. Converting JSON files and splitting training, validation, and test datasets with --val\_size and --test\_size
+### 1. Converting JSON files and splitting training, validation datasets
+
+You may need to place all LabelMe JSON files under **labelme\_json\_dir** and then run the following command:
+
+```shell
+labelme2yolo --json_dir /path/to/labelme_json_dir/
+```
+
+This tool will generate dataset labels and images with YOLO format in different folders, such as
+
+```plaintext
+/path/to/labelme_json_dir/YOLODataset/labels/train/
+/path/to/labelme_json_dir/YOLODataset/labels/val/
+/path/to/labelme_json_dir/YOLODataset/images/train/
+/path/to/labelme_json_dir/YOLODataset/images/val/
+/path/to/labelme_json_dir/YOLODataset/dataset.yaml
+```
+
+### 2. Converting JSON files and splitting training, validation, and test datasets with --val\_size and --test\_size
 
 You may need to place all LabelMe JSON files under **labelme\_json\_dir** and then run the following command:
 
@@ -53,33 +69,6 @@ This tool will generate dataset labels and images with YOLO format in different
 /path/to/labelme_json_dir/YOLODataset/images/train/
 /path/to/labelme_json_dir/YOLODataset/images/test/
 /path/to/labelme_json_dir/YOLODataset/images/val/
-
-/path/to/labelme_json_dir/YOLODataset/dataset.yaml
-```
-
-### 2. Converting JSON files and splitting training and validation datasets by folders
-
-If you have split the LabelMe training dataset and validation dataset on your own, please put these folders under **labelme\_json\_dir** as shown below:
-
-```plaintext
-/path/to/labelme_json_dir/train/
-/path/to/labelme_json_dir/val/
-```
-
-This tool will read the training and validation datasets by folder. You may run the following command to do this:
-
-```shell
-labelme2yolo --json_dir /path/to/labelme_json_dir/
-```
-
-This tool will generate dataset labels and images with YOLO format in different folders, such as
-
-```plaintext
-/path/to/labelme_json_dir/YOLODataset/labels/train/
-/path/to/labelme_json_dir/YOLODataset/labels/val/
-/path/to/labelme_json_dir/YOLODataset/images/train/
-/path/to/labelme_json_dir/YOLODataset/images/val/
-
 /path/to/labelme_json_dir/YOLODataset/dataset.yaml
 ```
 
@@ -94,4 +83,6 @@ hatch build
 
 ## License
 
+**Forked from [rooneysh/Labelme2YOLO](https://github.com/rooneysh/Labelme2YOLO)**
+
 `labelme2yolo` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
diff --git a/pyproject.toml b/pyproject.toml
index a354e92..74c2e1d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,18 +13,20 @@ authors = [
   { name = "GreatV(Wang Xin)", email = "xinwang614@gmail.com" },
 ]
 classifiers = [
-  "Development Status :: 4 - Beta",
+  "Development Status :: 5 - Production/Stable",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3.8",
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
-  "Programming Language :: Python :: Implementation :: CPython",
-  "Programming Language :: Python :: Implementation :: PyPy",
+  "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
+  "License :: OSI Approved :: MIT License",
 ]
 dependencies = [
   "opencv-python>=4.1.2",
   "Pillow>=9.2,<10.3",
-  "numpy>=1.23.1,<1.27.0"
+  "numpy>=1.23.1,<1.27.0",
+  "tqdm"
 ]
 dynamic = ["version"]
 
@@ -52,7 +54,7 @@ cov = "pytest --cov-report=term-missing --cov-config=pyproject.toml --cov=labelm
 no-cov = "cov --no-cov"
 
 [[tool.hatch.envs.test.matrix]]
-python = ["38", "39", "310"]
+python = ["38", "39", "310", "311", "312"]
 
 [tool.coverage.run]
 branch = true