NVIDIA / Imageinary
Imageinary is a reproducible mechanism which is used to generate large image datasets at various resolutions. The tool supports multiple image types, including JPEGs, PNGs, BMPs, RecordIO, and TFRecord files
☆27Updated 2 years ago
Alternatives and similar repositories for Imageinary:
Users that are interested in Imageinary are comparing it to the libraries listed below
- ☆16Updated 3 years ago
- Test data for DALI project☆42Updated 2 months ago
- Conversational AI Benchmark.☆68Updated last year
- Collection of models and extensions for deployment in PyTorch☆24Updated 2 years ago
- Hardware Accelerated Pytorch Container with (also accelerated) ffmpeg & OpenCV 4☆24Updated last year
- Utilities for sequential processing of tar files.☆24Updated 3 years ago
- Demonstration of using Caffe2 inside an Android application.☆10Updated 6 years ago
- Comparing PyTorch, JIT and ONNX for inference with Transformers☆18Updated 4 years ago
- ☆21Updated 5 years ago
- 3rd party dependencies for DALI project☆10Updated last week
- An open source implementation of CLIP.☆32Updated 2 years ago
- TPU enabled Tensorflow implementation of "Large Scale GAN Training for High Fidelity Natural Image Synthesis" (BigGAN)☆34Updated 4 years ago
- NVIDIA GPU Accelerated Application Samples in Google Cloud Platform☆19Updated 2 weeks ago
- This repository contains the results and code for the MLPerf™ Training v0.6 benchmark.☆42Updated last year
- Needles in Haystacks: On Classifying Tiny Objects in Large Images☆22Updated 5 years ago
- Tensors and Dynamic neural networks in Python with strong GPU acceleration☆17Updated last year
- PyTorch implementation of GLOM☆22Updated 3 years ago
- Implements EvoNorms B0 and S0 as proposed in Evolving Normalization-Activation Layers.☆11Updated 5 years ago
- A server powering LAION's effort to filter CommonCrawl with CLIP, building a large scale image-text dataset.☆13Updated 2 years ago
- Validation of the PyTorch -> ONNX -> Intel OpenVino workflow using pretrained ResNet-50☆45Updated 6 years ago