TensorRT YOLO v4.0 - Release Notes

Breaking Changes

• Add Dockerfile for building project Docker image (73060db)
• Add support for YOLOv3 and Ultralytics model export (8f2af94)
• Added Support for YOLOv10 (62071cb)
• Refactor deploy library (8a4df33)
• Use CUDA Graph to Accelerate Static Model Inference (3576c78)
• Refactor: Add BaseDet base class, refactor DeployDet and DeployCGDet (416e77b)
• Add streaming video support using VideoPipe (#17, #19)
• feat: major update with pybind11 integration and new 4.0 tag (3244eea)

Bug Fixes

• Fix incorrect time interval calculation (a3dee2a)
• Fix: Include <cstring> to resolve "memcpy is not a member of std" error in Linux (1b763d9)
• Update detection output variable names for clarity (fe67b01)
• Add cstdint to resolve Linux compilation issue (f602dc4)
• Fix: Graph input and output tensors must include dtype information. (2cacb7d)

Full Changelog: v3.0...v4.0

TensorRT YOLO v3.0 - Release Notes

Breaking Changes

• Add TensorRT INT8 PTQ support (87f67ff)
• Add C++ inference implementation (0f3069f)
• Implemented parallel preprocessing with multiple streams (86d6175)
• Refactor C++ inference code to support dynamic and static libraries (425a1a4)
• Refactored Python code related to TensorRT-YOLO and packaged it as tensorrt_yolo. (a10ebc8)

Bug Fixes

• Fix batch visualize bug (9125219)
• Remove deleted move constructor and move assignment operator (e287342)
• Fix duplicate imports (1237e21)
• Fix bug (24ea950)

Full Changelog: v2.0...v3.0

TensorRT YOLO v2.0 - Release Notes

Breaking Changes

• Implement YOLOv9 Export to ONNX and TensorRT with EfficientNMS Plugin (249bfab)
• Remove FLOAT16 ONNX export and add support for Dynamic Shape export (9ec1f29)
• Enable dynamic shape inference with CUDA Python and TensorRT 8.6.1 for inference (3286450)

Bug Fixes

• Fix bounding boxes rescales bug (0f90cd0)
• Fix AttributeError in YOLOv9 Model Export (#8)

Full Changelog: v1.0...v2.0

TensorRT YOLO v1.0 - Release Notes

Breaking Changes

• Supports FLOAT32, FLOAT16 ONNX export, and TensorRT inference
• Supports YOLOv5, YOLOv8, PP-YOLOE, and PP-YOLOE+
• Integrates EfficientNMS TensorRT plugin for accelerated post-processing
• Utilizes CUDA kernel functions to accelerate preprocessing
• Supports Python inference

Bug Fixes

• Fix pycuda.driver.CompileError on Jetson (#1)
• Fix Engine Deserialization Failed using YOLOv8 Exported Engine (#2)
• Fix Precision Anomalies in YOLOv8 FP16 Engine (#3)
• Fix YOLOv8 EfficientNMS output shape abnormality (0e542ee)
• Fix trtexec Conversion Failure for YOLOv5 and YOLOv8 ONNX Models on Linux) (#4)
• Fix Inference Anomaly Caused by preprocess.cu on Linux (#5)

Full Changelog: https://github.com/laugh12321/TensorRT-YOLO/commits/v1.0