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14 public repositories
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🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
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Jul 8, 2022
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🥂 Gracefully face hCaptcha challenge with YOLOv6(ONNX) embedded solution.
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Jul 6, 2022
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Python
🔥🔥🔥 A collection of some awesome YOLO object detection series projects.
A set of tools for converting a yolov5 format dataset to COCO format working with yolov5, yolox and yolov6.
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Jul 6, 2022
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tensorrt for yolov7,yolov6,yolov5,yolox
C++ implementation of YOLOv6 using TensorRT
Deep Learning Model Optimization Using by TensorRT API, window
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Jul 4, 2022
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Python
YOLOv5 of PaddleDetection, Paddle implementation by the official team of PaddleDetection.
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Jul 1, 2022
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分别使用OpenCV、ONNXRuntime部署YOLOV6目标检测，包含C++和Python两个版本的程序
🌀 🌀 手摸手 美团 YOLOv6模型训练和TensorRT端到端部署方案教程
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Jun 30, 2022
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A simple implementation of Tensorrt MT-YOLOv6
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Jul 6, 2022
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Python
fire detection with yoloR
MT-Yolov6 TensorRT Inference with Python.
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Jul 2, 2022
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Python
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这个issue主要讲一下，如何把你自己的模型添加到lite.ai.toolkit。lite.ai.toolkit集成了一些比较新的基础模型，比如人脸检测、人脸识别、抠图、人脸属性分析、图像分类、人脸关键点识别、图像着色、目标检测等等，可以直接用到具体的场景中。但是，毕竟lite.ai.toolkit的模型还是有限的，具体的场景下，可能有你经过优化的模型，比如你自己训了一个目标检测器，可能效果更好。那么，如何把你的模型加入到lite.ai.toolkit中呢？这样既能用到lite.ai.toolkit一些已有的算法能力，也能兼容您的具体场景。这个issue主要是讲这个问题。大家有疑惑的可以提在这个issue，我会尽可能回答~