#jupyter_notebook #coreml #ios #object_detection #onnx #pytorch #tflite #yolov3 #yolov4 #yolov5

https://github.com/ultralytics/yolov5

#cplusplus #vgg #resnet #alexnet #squeezenet #inceptionv3 #googlenet #resnext #tensorrt #crnn #senet #arcface #mobilenetv2 #yolov3 #shufflenetv2 #mnasnet #retinaface #mobilenetv3 #yolov3_spp #yolov4 #yolov5

https://github.com/wang-xinyu/tensorrtx

#python #real_time #video #pytorch #computer_camera #rtsp_stream #web_camera #you_only_look_once #pedestrian_tracking #deep_sort #http_stream #multple_object_tracking #deep_association_metric #yolov5 #simple_online_and_realtime_tracking #pytorch_yolov5 #yolo_v5

https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch

#python #coco #computer_vision #conda #deep_learning #detectron2 #instance_segmentation #jupyter_notebook #large_image #machine_learning #mmdetection #object_detection #pip #pytorch #small_object_detection #yolov5

https://github.com/obss/sahi

#cplusplus #android #deep_learning #deployment #graphcore #intel #ios #jetson #kunlun #object_detection #onnxruntime #openvino #picodet #rockchip #sdk #serving #tensorrt #uie #yolov5

https://github.com/PaddlePaddle/FastDeploy

#jupyter_notebook #computer_vision #deep_learning #deep_neural_networks #image_classification #image_segmentation #object_detection #pytorch #tutorial #yolov5 #yolov6 #yolov7

https://github.com/roboflow-ai/notebooks

#python #object_detection #pytorch #rtmdet #yolo #yolov5 #yolov6 #yolox

https://github.com/open-mmlab/mmyolo

#python #damo_yolo #deep_learning #imagenet #nas #object_detection #onnx #pytorch #tensorrt #yolo #yolov5

https://github.com/tinyvision/DAMO-YOLO

#python #coreml #deep_learning #ios #machine_learning #ml #object_detection #onnx #pytorch #tflite #ultralytics #yolo #yolov3 #yolov5

YOLOv5 is a powerful and easy-to-use AI model for object detection, image segmentation, and classification. It is designed to be fast, accurate, and simple to implement. Here are the key benefits YOLOv5 is straightforward to set up and use, with detailed documentation and tutorials available.
- **Performance** You can use YOLOv5 for object detection, image segmentation, and classification tasks.
- **Community Support** You can run YOLOv5 in various environments such as Google Colab, Paperspace, Kaggle, and Docker.

Overall, YOLOv5 simplifies the process of integrating advanced AI capabilities into your projects.

https://github.com/ultralytics/yolov5

#cplusplus #caffe #convolution #deep_learning #deep_neural_networks #diy #graph_algorithms #inference #inference_engine #maxpooling #ncnn #pnnx #pytorch #relu #resnet #sigmoid #yolo #yolov5

This course, "_动手自制大模型推理框架_" (Handcrafting Large Model Inference Framework), is a valuable resource for those interested in deep learning and model inference. It teaches you how to build a modern C++ project from scratch, focusing on designing and implementing a deep learning inference framework. The course supports latest models like LLama3.2 and Qwen2.5, and uses CUDA acceleration and Int8 quantization for better performance.

By taking this course, you will learn how to write efficient C++ code, manage projects with CMake and Git, design computational graphs, implement common operators like convolution and pooling, and optimize them for speed. This knowledge will be highly beneficial for job interviews and advancing your skills in deep learning. The course also includes practical demos on models like Unet and YoloV5, making it a hands-on learning experience.

https://github.com/zjhellofss/KuiperInfer

#python #deep_learning #plate_recognition #pytorch #yolov5

This tool helps you detect and recognize car license plates from images and videos. It supports 12 different types of Chinese license plates, including blue, yellow, new energy, police, and more. You can use it with Python and PyTorch, and it provides demos for testing with images and videos. The benefit is that it makes it easy to automate the process of identifying car license plates accurately, which can be useful for various applications such as traffic management or security systems.

https://github.com/we0091234/Chinese_license_plate_detection_recognition