SPEED SAM C++ TENSORRT

🌐 Overview

📢 Updates

Model Conversion: Build TensorRT engines from ONNX models for accelerated inference.
Segmentation with Points and BBoxes: Easily segment images using selected points or bounding boxes.
FP16 Precision: Choose between FP16 and FP32 for speed and precision balance.
Dynamic Shape Support: Efficient handling of variable input sizes using optimization profiles.
CUDA Optimization: Leverage CUDA for preprocessing and efficient memory handling.

📢 Performance

Infernce Time

Results

📂 Project Structure

SPEED-SAM-CPP-TENSORRT/
├── include
│ ├── config.h # Model configuration and macros
│ ├── cuda_utils.h # CUDA utility macros
│ ├── engineTRT.h # TensorRT engine management
│ ├── logging.h # Logging utilities
│ ├── macros.h # API export/import macros
│ ├── speedSam.h # SpeedSam class definition
│ └── utils.h # Utility functions for image handling
├── src
│ ├── engineTRT.cpp # Implementation of the TensorRT engine
│ ├── main.cpp # Main entry point
│ └── speedSam.cpp # Implementation of the SpeedSam class
└── CMakeLists.txt # CMake configuration

🚀 Installation

Prerequisites

git clone https://github.com/hamdiboukamcha/SPEED-SAM-C-TENSORRT.git
cd SPEED-SAM-CPP-TENSORRT
# Create a build directory and compile
mkdir build && cd build
cmake ..
make -j$(nproc)

📦 Dependencies

CUDA: NVIDIA's parallel computing platform
TensorRT: High-performance deep learning inference
OpenCV: Image processing library
C++17: Required standard for compilation

🔍 Code Overview

Main Components

SpeedSam Class (speedSam.h): Manages image encoding and mask decoding.
EngineTRT Class (engineTRT.h): TensorRT engine creation and inference.
CUDA Utilities (cuda_utils.h): Macros for CUDA error handling.
Config (config.h): Defines model parameters and precision settings.

Key Functions

EngineTRT::build: Builds the TensorRT engine from an ONNX model.
EngineTRT::infer: Runs inference on the provided input data.
SpeedSam::predict: Segments an image using input points or bounding boxes.

📞 Contact

📜 Citation

 @misc{boukamcha2024SpeedSam,
 author = {Hamdi Boukamcha},
 title = {SPEED-SAM-C-TENSORRT},
 year = {2024},
 publisher = {GitHub},
 howpublished = {\url{https://github.com/hamdiboukamcha/SPEED-SAM-C-TENSORRT//}},
 }