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automl

Google Brain AutoML

awesome-crowd-counting

Awesome Crowd Counting

bayesian-crowd-counting

Official Implement of ICCV 2019 oral paper Bayesian Loss for Crowd Count Estimation with Point Supervision

c-3-framework

An open-source PyTorch code for crowd counting

crowdcount-cascaded-mtl

Single Image Crowd Counting (CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting)

crowdcount-mcnn

Single Image Crowd Counting via MCNN (Unofficial Implementation)

crowdcount-stackpool

Stacked pooling for crowd counting

darknet

Yolo v4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used)

gcc-sfcn

This is the official code of spatial FCN in the paper Learning from Synthetic Data for Crowd Counting in the Wild [CVPR2019].

gradient-centralization

A New Optimization Technique for Deep Neural Networks

labelme2dataset

Converts the semantic segmentation data annotated with Labelme to COCO or Cityscapes

learning-to-see-in-the-dark

Learning to See in the Dark. CVPR 2018

lsc-cnn

models

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

mscnn

mscnn crowd counting model implementation, source from "Multi-scale Convolution Neural Networks for Crowd Counting" write by Zeng L, Xu X, Cai B, et al.

netron

Visualizer for neural network, deep learning and machine learning models

opencv_contrib

Repository for OpenCV's extra modules

pcl

Point Cloud Library (PCL)

prepare_detection_dataset

convert dataset to coco/voc format

ssd

High quality, fast, modular reference implementation of SSD in PyTorch

ssd-se-cbam-resnet-feature_fusion

SSD的改进：加入attention机制——SE或者CBAM；Feature Fusion

yolov3

YOLOv3 in PyTorch > ONNX > CoreML > iOS

yolov5

YOLOv5 in PyTorch > ONNX > CoreML > iOS