dongyaolin Goto Github PK

augly

A data augmentations library for audio, image, text, and video.

capsvoxgan

GAN using capsule networks to generate voxel models

chatgpt_academic

科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持markdown表格显示，Tex公式双显示，代码显示功能完善，新增本地Python工程剖析功能/自我剖析功能

crawlcnki

爬取知网论文

dataaugmentationforobjectdetection

Data Augmentation For Object Detection

deep-learning-computer-vision

Personal implementation for Stanford CS231n / Umich: Deep Learning for Computer Vision (by Justin Johnson)

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

eecs598-008-dlcv

Deep Learning For Computer Vision Winter 2022 By Prof. Justin Johnson

face-nn

游戏捏脸，基于神经风格迁移框架生成逼真人脸

gfpgan

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

imgaug

Image augmentation for machine learning experiments.

labelme

automatic tagging data, the training data prepare for mask-rcnn

labelme2datasets

用于将LabelMe标注好的数据转换为VOC格式和COCO格式的数据集。

leather-texture-classification

这个项目基于深度学习技术，旨在识别和分类各种皮革纹理。无论您是从事时尚设计、工业制造还是艺术创作，这个项目将为您提供一个高效的纹理分类系统。

lhy_machine_learning

李宏毅2021春季机器学习课程课件及作业

machinelearningdeeplearning

李宏毅2021机器学习深度学习笔记PPT作业

mvss-net

code for Image Manipulation Detection by Multi-View Multi-Scale Supervision

new-yolov1_pytorch

od-annotation

目标检测数据集标注工具

pige

pigepipei

python-machine-learning

机器学习算法项目

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

shenlan

stylegan3

to_do_list

任务记事板是一个简单的待办事项管理工具，使用 Python 的 Tkinter 库创建了一个基本的图形用户界面。

voc_to_coco

最简单的VOC转COCO， 一条指令完整转换

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

yolox

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/