
AlexeyAB/darknet: YOLOv4 / Scaled-YOLOv4 / YOLO - GitHub
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet ) - AlexeyAB/darknet
A complete guide to object detection using YOLO V4 and OpenCV
A complete guide to object detection using YOLO V4 and OpenCV. This collection of Google Colab-Notebooks demonstrates how to perform object detection using the YOLO V4 model. The material is seperated in two sections as listed below:
AllanYiin/YoloV4: Yolo v4 in pytorch, tensorflow and onnx - GitHub
pytorch_yolo.py: it is just a basic library derived from trident , to define darknet and yolo basic block. pytorch_darknet.py: we can construction yolo v4 network and load pretrained weights here. pytorch_infer_yolo4.py: It's a demo to show how to do object detection by yolo v4 model and how trident api to make things easy.
WongKinYiu/PyTorch_YOLOv4: PyTorch implementation of …
track-yolo; 2020-11-23 - support teacher-student learning. 2020-11-17 - pytorch 1.7 compatibility. 2020-11-06 - support inference with initial weights. 2020-10-21 - fully supported by darknet. 2020-09-18 - design fine-tune methods. 2020-08-29 - support deformable kernel. 2020-08-25 - pytorch 1.6 compatibility. 2020-08-24 - support channel last ...
yolov4 · GitHub Topics · GitHub
2024年11月6日 · Multi-camera live traffic and object counting with YOLO v4, Deep SORT, and Flask. opencv flask tracking livestream traffic yolo object-detection object-tracking traffic-monitoring real-time-analytics traffic-counter people-counter camera-stream deep-sort imagezmq yolov4 yolo-v4 traffic-counting yolov4-cloud yolov4-deepsort
maudzung/Complex-YOLOv4-Pytorch - GitHub
2020年8月26日 · Velodyne point clouds (29 GB): input data to the Complex-YOLO model; Training labels of object data set (5 MB): input label to the Complex-YOLO model; Camera calibration matrices of object data set (16 MB): for visualization of predictions; Left color images of object data set (12 GB): for visualization of predictions
machine-learning-papers-summary/cv/yolo-v4.md at master
CutMix is to cover the cropped image to rectangle region of other images, and adjusts the label according to the size of the mix area. Mosaic represents a new data augmentation method that mixes 4 training images, while CutMix mixes only 2 input images. As …
GitHub - Tianxiaomo/pytorch-YOLOv4: PyTorch ,ONNX and …
├── README.md ├── dataset.py dataset ├── demo.py demo to run pytorch --> tool/darknet2pytorch ├── demo_darknet2onnx.py tool to convert into onnx --> tool/darknet2pytorch ├── demo_pytorch2onnx.py tool to convert into onnx ├── models.py model for pytorch ├── train.py train models.py ├── cfg.py cfg ...
RobotEdh/Yolov-4: Yolo v4 using TensorFlow 2.x - GitHub
Same logic than Yolo v4 but with only 26 layers and 2 output layers. All the steps are included in the jupyter notebooks YoloV3-tiny_tf.ipynb and YoloV3-tiny_Train_tf.ipynb The steps to create your own data for training a model are the following
Pretrained YOLO v4 Network For Object Detection - GitHub
YOLO v4 network architecture is comprised of three sections i.e. Backbone, Neck and Detection Head. Backbone: CSP-Darknet53(Cross-Stage-Partial Darknet53) is used as the backbone for YOLO v4 networks. This is a model with a higher input resolution (608 x 608), a larger receptive field size (725 x 725), a larger number of 3 x 3 convolutional ...