This project is still in progress. If you are looking for the working code, use BEGAN-tensorflow. Requirements Usage First download CelebA datasets with: $ apt-get install p7zip-full # ubuntu $ brew install p7zip # Mac $ python download.py or you can use your own dataset by placing images like: data └── YOUR_DATASET_NAME ├── xxx.jpg (name doesn’t matter) ├── yyy.jpg └── … To train a model:

A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If you’re interested in C++ inference, move HERE Results Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Accuracy 54000 GTX 1080 Ti 512 0.16 100 625 0.9 ~1700 95.65% Sample $ python infer.py -c=./logs/model-54000.pth ./images/test-75.png length: 2 digits: 7 5 10 10 10

Code accompanying the paper “Wasserstein GAN” A few notes The first time running on the LSUN dataset it can take a long time (up to an hour) to create the dataloader. After the first run a small cache file will be created and the process should take a matter of seconds. The cache is a list of indices in the lmdb database (of LSUN) The only addition to the code (that we forgot, and will add, on the paper) are […]

This repo is implementation for PointNet(https://arxiv.org/abs/1612.00593) in pytorch. The model is in pointnet/model.py. It is tested with pytorch-1.0. git clone https://github.com/fxia22/pointnet.pytorch cd pointnet.pytorch pip install -e . Download and build visualization tool cd script bash build.sh #build C++ code for visualization bash download.sh #download dataset Training cd utils python train_classification.py –dataset –nepoch= –dataset_type python train_segmentation.py –dataset –nepoch= Use –feature_transform to use feature transform. Classification performance On ModelNet40: Overall Acc Original implementation 89.2 this implementation(w/o feature transform) 86.4 this implementation(w/ feature […]