# tensorflow_Resnet_train_test

**Repository Path**: cuzjx/tensorflow_Resnet_train_test

## Basic Information

- **Project Name**: tensorflow_Resnet_train_test
- **Description**: Code for training different architectures( DenseNet, ResNet, AlexNet, GoogLeNet, VGG, NiN) on your own dataset + Multi-GPU support + batch and single image testing support
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-12-25
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# tensorflow_Resnet_train_test
Code for training different architectures( DenseNet, ResNet, AlexNet, GoogLeNet, VGG, NiN) on your own dataset + Multi-GPU support + batch and single image testing support

This repository provides an easy-to-use way for training and testing different well-known deep learning architectures on your own datasets.
The code directly load images from disk. Moreover, multi-GPU and transfer learning is also supported, also, you can choose testing images in batch or single.

Based on repository:

https://github.com/arashno/tensorflow_multigpu_imagenet


#Example of usages:


Training:

  1. Prepare training data list:
    python train_val_datalist_creater.py

  2. training or Transfer learning:
    python train.py




Testing:

    python eval.py



or Testing in batch:

1. Prepare testing data list:

    python train_val_datalist_creater.py --create_data val

2. testing in batch:

    python eval.py --eval_model True


model download:  https://pan.baidu.com/s/1BECiZgsiiCkf3kAyPJkIlA