add v0.19.1 release

docs/source/tv_tensors.rst

+.. _tv_tensors:
+
+TVTensors
+==========
+
+.. currentmodule:: torchvision.tv_tensors
+
+TVTensors are :class:`torch.Tensor` subclasses which the v2 :ref:`transforms
+<transforms>` use under the hood to dispatch their inputs to the appropriate
+lower-level kernels. Most users do not need to manipulate TVTensors directly.
+
+Refer to
+:ref:`sphx_glr_auto_examples_transforms_plot_transforms_getting_started.py` for
+an introduction to TVTensors, or
+:ref:`sphx_glr_auto_examples_transforms_plot_tv_tensors.py` for more advanced
+info.
+
+.. autosummary::
+    :toctree: generated/
+    :template: class.rst
+
+    Image
+    Video
+    BoundingBoxFormat
+    BoundingBoxes
+    Mask
+    TVTensor
+    set_return_type
+    wrap

docs/source/utils.rst

-torchvision.utils
-=================
+.. _utils:
 
-.. currentmodule:: torchvision.utils
+Utils
+=====
 
-.. autofunction:: make_grid
+The ``torchvision.utils`` module contains various utilities, mostly :ref:`for
+visualization <sphx_glr_auto_examples_others_plot_visualization_utils.py>`.
 
-.. autofunction:: save_image
+.. currentmodule:: torchvision.utils
 
-.. autofunction:: draw_bounding_boxes
+.. autosummary::
+    :toctree: generated/
+    :template: function.rst
 
-.. autofunction:: draw_segmentation_masks
+    draw_bounding_boxes
+    draw_segmentation_masks
+    draw_keypoints
+    flow_to_image
+    make_grid
+    save_image

examples/cpp/CMakeLists.txt

+cmake_minimum_required(VERSION 3.10)
+project(run_model)
+
+option(USE_TORCHVISION "Whether to link to torchvision" OFF)
+
+find_package(Torch REQUIRED)
+if(USE_TORCHVISION)
+  find_package(TorchVision REQUIRED)
+endif()
+
+add_executable(run_model run_model.cpp)
+
+target_link_libraries(run_model "${TORCH_LIBRARIES}")
+if(USE_TORCHVISION)
+  target_link_libraries(run_model TorchVision::TorchVision)
+endif()
+
+set_property(TARGET run_model PROPERTY CXX_STANDARD 17)

examples/cpp/hello_world/CMakeLists.txt

-cmake_minimum_required(VERSION 3.10)
-project(hello-world)
-
-# The first thing do is to tell cmake to find the TorchVision library.
-# The package pulls in all the necessary torch libraries,
-# so there is no need to also add `find_package(Torch)` here.
-find_package(TorchVision REQUIRED)
-
-add_executable(hello-world main.cpp)
-
-# We now need to link the TorchVision library to our executable.
-# We can do that by using the TorchVision::TorchVision target,
-# which also adds all the necessary torch dependencies.
-target_compile_features(hello-world PUBLIC cxx_range_for)
-target_link_libraries(hello-world TorchVision::TorchVision)
-set_property(TARGET hello-world PROPERTY CXX_STANDARD 14)

examples/cpp/hello_world/README.rst

-Hello World!
-============
-
-This is a minimal example of getting TorchVision to work in C++ with CMake.
-
-
-In order to successfully compile this example, make sure you have both ``LibTorch`` and
-``TorchVision`` installed.
-Once both dependencies are sorted, we can start the CMake fun:
-
-1) Create a ``build`` directory inside the current one.
-2) from within the ``build`` directory, run the following commands:
-    - | ``cmake -DCMAKE_PREFIX_PATH="<PATH_TO_LIBTORCH>;<PATH_TO_TORCHVISION>" ..``
-      | where ``<PATH_TO_LIBTORCH>`` and ``<PATH_TO_TORCHVISION>`` are the paths to the libtorch and torchvision installations.
-    - ``cmake --build .``
-
-| That's it!
-| You should now have a ``hello-world`` executable in your ``build`` folder.
- Running it will output a (fairly long) tensor of random values to your terminal.
\ No newline at end of file

examples/cpp/hello_world/main.cpp

-#include <iostream>
-#include <torch/torch.h>
-#include <torchvision/vision.h>
-#include <torchvision/models/resnet.h>
-
-int main()
-{
-  auto model = vision::models::ResNet18();
-  model->eval();
-
-  // Create a random input tensor and run it through the model.
-  auto in = torch::rand({1, 3, 10, 10});
-  auto out = model->forward(in);
-
-  std::cout << out.sizes();
-
-  if (torch::cuda::is_available()) {
-    // Move model and inputs to GPU
-    model->to(torch::kCUDA);
-    auto gpu_in = in.to(torch::kCUDA);
-    auto gpu_out = model->forward(gpu_in);
-
-    std::cout << gpu_out.sizes();
-  }
-}

gallery/assets/coco/images/000000000001.jpg

+../../astronaut.jpg
\ No newline at end of file