Pinned Repositories
Android_MobileNetV2-YOLOV3-Nano-NCNN
MobileNetV2-YOLOV3-Nano NCNN sample
Android_NCNN_yolov4-tiny
yolov4-tiny ncnn android sample
FastestDet
:zap: A newly designed ultra lightweight anchor free target detection algorithm, weight only 250K parameters, reduces the time consumption by 10% compared with yolo-fastest, and the post-processing is simpler
MobileNet-Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
simple-rknn2
The rknn2 API uses the secondary encapsulation of the process, which is easy for everyone to call. It is applicable to rk356x rk3588
Simple-TensorRT
Secondary encapsulation of NVIDIA TensorRT interface to simplify the calling process
Ultralight-SimplePose
Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,
Yolo-Fastest
:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+
Yolo-FastestV2
:zap: Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
yolov3
支持MobileNetV2-YOLO训练
dog-qiuqiu's Repositories
dog-qiuqiu/Android_NCNN_yolov4-tiny
yolov4-tiny ncnn android sample
dog-qiuqiu/yolov3
支持MobileNetV2-YOLO训练
dog-qiuqiu/Android_MobileNetV2-YOLOV3-Nano-NCNN
MobileNetV2-YOLOV3-Nano NCNN sample
dog-qiuqiu/YOLOv5_NCNN
🍅 移动端部署,支持YOLOv5s、YOLOv4-tiny、MobileNetV2-YOLOv3-nano、Simple-Pose与Yolact模型,支持iOS、Android,使用NCNN框架。
dog-qiuqiu/DBFace
DBFace is a real-time, single-stage detector for face detection, with faster speed and higher accuracy
dog-qiuqiu/caffe
Add yolov3 upsampler layer
dog-qiuqiu/cocodata_yolo_train
coco2017数据集官方json标签文件转yolo训练的txt标签文件
dog-qiuqiu/Face-Detector-1MB-with-landmark
1M人脸检测模型(含关键点)
dog-qiuqiu/DenseNet-Caffe
DenseNet Caffe Models, converted from https://github.com/liuzhuang13/DenseNet
dog-qiuqiu/Dynamic-Face-Recognition
Deep learning,Face recognition algorithm based on Mobilenet and Mtcnn(LFW 99.1%, Mobilenet-based face recognition model is superior to the accuracy of the original centerloss paper)
dog-qiuqiu/gluon-cv
Gluon CV Toolkit
dog-qiuqiu/MTCNN_face_detection_alignment
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
dog-qiuqiu/rknn-toolkit
dog-qiuqiu/YOLOV3-Detection
PyCaffe object detection (Based on YOLOV3)