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

https://github.com/ultralytics/yolov5

#python #darknet2onnx #darknet2pytorch #onnx #pytorch #pytorch_yolov4 #tensorrt #yolov4

https://github.com/Tianxiaomo/pytorch-YOLOv4

#python #blazeface #cascade_rcnn #cbnet #cornernet_lite #efficientdet #face_detection #faceboxes #faster_rcnn #fcos #gcnet #instance_segmentation #libra_rcnn #mask_rcnn #object_detection #pp_yolo #retinanet #ssd #ttfnet #yolov3 #yolov4

https://github.com/PaddlePaddle/PaddleDetection

#python #pytorch #yolo #implicit #representation #darknet #explicit #yolov4 #scaled_yolov4 #yolov4_csp #yolor #unified_network

https://github.com/WongKinYiu/yolor

#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 #darknet #pytorch #scaled_yolov4 #yolor #yolov3 #yolov4 #yolov7

https://github.com/WongKinYiu/yolov7

#jupyter_notebook #darknet #pytorch #scaled_yolov4 #yolor #yolov3 #yolov4 #yolov7

YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments.

https://github.com/WongKinYiu/yolov7