Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Mask_rcnn | 23,745 | 10 months ago | 5 | March 05, 2019 | 1,993 | other | Python | |||
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | ||||||||||
Deep Learning With Keras Notebooks | 1,868 | 6 years ago | 1 | Jupyter Notebook | ||||||
Jupyter notebooks for using & learning Keras | ||||||||||
Efficientdet | 1,306 | 2 years ago | 2 | apache-2.0 | Python | |||||
EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow | ||||||||||
Keras_cv_attention_models | 523 | 1 | 9 months ago | 94 | November 21, 2023 | 2 | mit | Python | ||
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tinynet,tinyvit,uniformer,volo,vanillanet,yolor,yolov7,yolov8,yolox,gpt2,llama2, alias kecam | ||||||||||
Yolo3 Keras | 523 | 2 years ago | 45 | mit | Python | |||||
这是一个yolo3-keras的源码,可以用于训练自己的模型。 | ||||||||||
Yolov4 Keras | 498 | a year ago | 64 | mit | Python | |||||
这是一个YoloV4-keras的源码,可以用于训练自己的模型。 | ||||||||||
Nocs_cvpr2019 | 346 | 2 years ago | 20 | other | Python | |||||
[CVPR2019 Oral] Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation on Python3, Tensorflow, and Keras | ||||||||||
Keras Maskrcnn | 330 | 6 | 1 | 5 years ago | 2 | June 20, 2019 | 15 | apache-2.0 | Python | |
Keras implementation of MaskRCNN object detection. | ||||||||||
Pose Residual Network | 316 | 6 years ago | 11 | Python | ||||||
Code for the Pose Residual Network introduced in 'MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network (ECCV 2018)' paper | ||||||||||
Keras Yolov4 | 309 | 4 years ago | 33 | Python | ||||||
yolov4 42.0% mAP.ppyolo 45.1% mAP. |