Releases: henryzhuhr/deep-object-detect-track
Releases · henryzhuhr/deep-object-detect-track
v1.1.0 (2024.6.7)
Major Features and Improvements Summary
New Features:
- Added semi-automatic annotation assistant tool
📎 Attachment:
- Original yolov5s exported model
- A sample dataset available for download
- Model trained using the sample dataset and its exported model
主要功能和改进摘要
新功能:
- 新增半自动化标注辅助工具
📎 附件:
- 原始 yolov5s 导出模型
- 一个样本数据集可供下载
- 使用样本数据集训练的模型及其导出模型
v1.0.0 (2024.6.3)
Major Features and Improvements Summary
Features:
- Automatically create and activate python environment for training and inference.
- Object detection (Yolov5) and tracking(BYTETrack) algorithms are supported.
- Tutorials for preparing dataset.
- Train model with custom dataset.
Deployment support:
- ONNXRuntime: inference with ONNXruntime are supported.
- Openvino: inference with Openvino 2024.1.0 is supported, the previous version has not been rigorously tested.
- TensorRT: inference with TensorRT 10.0.1 and 8.6.1 are supported.
📎 Attachment:
- A sample dataset is prepared for download.
主要功能和改进摘要
功能:
- 自动创建和激活 python 环境进行训练和推理。
- 支持目标检测(Yolov5)和跟踪(BYTETrack)算法。
- 准备数据集的教程。
- 训练自己的数据集
部署支持:
- ONNXRuntime:支持 ONNXruntime 的推理。
- Openvino:支持使用 Openvino 2024.1.0 进行推理,对于先前的版本没有经过严格测试,
- TensorRT:支持 TensorRT 10.0.1 和 8.6.1 的推理。
📎 附件:
- 准备了一个示例数据集以供下载。