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This is a cinputer vision deep learning experimental platform for Pytorch. With just one line of Linux command you can do the following:
- Train a neural network for muilti classifion task with single or muilti GPUs.
- Use acc, precision, recall, f1 score, confusion matrix to evaluate the model.
- Use tensorboard to record and visualize model performance.
- Save each checkpoint.
- Save the best performing model.
- Save the prediction result for each evaluation.
In addition, this platform is flexible:
- Easy to change other datasets.
- Modify
net.py
to change or customize your network. - Modify output layer in
net.py
and loss function inloss.py
to change the task to single classification or regression task.
[name=weidaolee]
Python 3.6.0 or later with all of the env/requirments.txt
torch==1.2.0
torchvision==0.4.0
tensorboardX==1.8
tensorboard==1.14.0
Clone and install requirements
$ git clone https://github.com/weidaolee/classification_platform.git
$ pip install -r env/requirements.txt
Modify configs and paths
$ vim config/defualt.cfg
$ python train.py -h ## show this help message and exit
$ train.py [-h] [--prefix PREFIX] [--gpu GPU] [--cfg CFG]
[--weights_path WEIGHTS_PATH] [--n_cpu N_CPU]
[--checkpoint CHECKPOINT] [--checkpoint_dir CHECKPOINT_DIR]
[--tfboard TFBOARD]`
$ cd logs
$ tensorboard [--logdir PREFIX] [--port PORT]
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