emptysoal

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@emptysoal

TensorRT-YOLO11. Based on tensorrt v8.0+, deploy detection, pose, segment, tracking of YOLO11 with C++ and python api.

340

TensorRT-YOLOv8-ByteTrack. An object tracking project with YOLOv8 and ByteTrack, speed up by C++ and TensorRT.

247

TensorRT-YOLOv8. Based on tensorrt v8.0+, deploy detect, pose, segment, tracking of YOLOv8 with C++ and python api.

149

cuda-image-preprocess. Speed up image preprocess with cuda when handle image or tensorrt inference

85

tensorrt-experiment. Base on tensorrt version 8.2.4, compare inference speed for different tensorrt api.

55

VideoRestore. Enhance video resolution

38

Deepsort-YOLOv5-TensorRT. An object tracking project with YOLOv5-v5.0 and Deepsort, speed up by C++ and TensorRT.

16

YOLOv5-TensorRT-lib-Python. The code of YOLOv5 inferencing with TensorRT C++ api is packaged into a dynamic link library , then called through Python.

15

TensorRT-v8-YOLOv5-v5.0. Based on TensorRT v8.2, build network for YOLOv5-v5.0 by myself, speed up YOLOv5-v5.0 inferencing

14

keypoint-resnet50. Based on ResNet50, detect keypoint, and use keypoint perspective transform image.

12

vit-tensorrt. Python

8

LLM-TRAINING. LLM SFT and RLHF

6

lstm-torch2trt. Build a simple LSTM example using pytorch, and then convert the model in pytorch format to onnx and tensorrt format, in turn.

4

Coco-Mask-Transform. Coco标注格式和Mask标注格式相互转换

4

concurrent_communion. python socket concurrent mysql

3

vLLM-Milvus-RAG. Implement RAG using vLLM + Milvus

3

PyTorch-Resnet. PyTorch-Resnet

2

Kafka-Docker-Python. 使用docker构建kafka环境,并通过python调用kafka接口

1

mask-rcnn-pytorch. Python

1

Flask-Gunicorn-Nginx. Flask配合Nginx部署示例

1

text-generation-webui-customized. text generation webui customized

1

RabbitMQ-Docker-Python. 在docker中分别构建rabbitMQ和python环境,并通过python调用rabbitMQ

1

MultiModal-RAG. A multimodal RAG system that achieves a complete closed loop of mixed understanding of text and images, intelligent routing, and visual interaction.

1

Advanced-RAG. A variety of different rag schemes have been implemented using workflow and agent

1
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