Implementation of cats-vs-dogs based on CNN.

A simple Lightning Memory-Mapped Database (LMDB) converter for ImageFolder datasets in PyTorch. Using LMDB over a regular file structure improves I/O performance significantly. Works on both Windows and Linux. Comes with latest Python support.

Transfer Learning on Dogs vs Cats dataset using PyTorch C+ API

Dogs Vs Cats Classifier for Kaggle Competition

Dog vs Cat classifier Flask app using Convolutional Neural Network with pretrained model MobileNetV2 from Keras. Model has 98% accuracy on both train and validation sets. Heroku app at https://dogvscat-mobilenet.herokuapp.com/

Pytorch implementation for Dogs vs. Cats Redux: Kernels Edition, Kaggle competition. Modified from Image Classification with Pytorch. Homework of Deep Learning, UCAS course 081203M05009H. Kaggle猫狗分类比赛的Pytorch实现, 修改自Image Classification with Pytorch, 中国科学院大学深度学习作业.

🦞 图像分类任务（支持 API 部署）

Dog and cat breed names

A flask based web application to differentiate between cats and dogs

使用深度学习方法识别一张图片是猫还是狗。

My solution to the Kaggle challenge "Dogs vs. Cats" using PyTorch.

An exemplar repo generated and written in golang with an openapi spec

s small deep_learning practice

An image classifier that determines whether an image contains a dog or a cat.

Usage of CNN to build a Cat vs Dog Model

Kaggle Classification Challenge on classifying dogs and cats using Transfer Learning.

A cat vs dog image classifier built with keras and then exported to be used in the browser by tensorflow.js

Kaggle competition dogs-vs-cats. Implemented Logistic Regression and InceptionV3 (transfer learning).