#python #bounding_boxes #computer_vision #data_augmentation #data_visualization #deep_learning #deep_neural_networks #image_processing #k_means #mean_average_precision #numpy #object_detection #pandas #performance_visualization #pretrained_weights #python3 #random_weights #tensorflow2 #train #yolo #yolov3

https://github.com/emadboctorx/yolov3-keras-tf2

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

https://github.com/ultralytics/yolov5

#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 #deep_neural_networks #deployment #detection #neural_networks #classification #segmentation #resnet #deeplearning #unet #industry #jetson #mobilenet #yolov3

https://github.com/PaddlePaddle/PaddleX

#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 #tensorrt #ncnn #onnx #yolov3 #openvino #yolox #yolox_nano

https://github.com/Megvii-BaseDetection/YOLOX

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

https://github.com/WongKinYiu/yolov7

#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

#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