.. # SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. .. _v0.1.0-prealpha: PreAlpha ======== CV-CUDA-0.1.0 is the first release of CV-CUDA. This release is for evaluation purposes only. Release Highlights ------------------ This CV-CUDA release includes the following key features: * Core components including Image and Tensor with Batch support * Utilities to help write CUDA kernels * 6 Operators - Reformat, Resize, Custom Crop, Normalize, PadAndStack, ConvertTo * Tensor interoperability with pytorch/gpu, Image interoperability with pytorch/gpu, pillow/cpu, opencv/cpu * Python bindings * Sample applications * API documentation Compatibility ------------- This section highlights the compute stack CV-CUDA has been tested on * Ubuntu x86 >= 20.04 * CUDA driver >= 11.7 The Sample applications based on TensorRT have been tested with TensorRT >= 8.5 Known Issues ------------ * There will be few updates in the Tensor API, Image Formats and Operator names in the next release * Limitations in the usage of the operators which are described in the API documentation License ------- Nvidia Software Evaluation License