Merge branch 'main' into trivialaugment_implementation

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -0,0 +1,60 @@
+name: 🐛 Bug Report
+description: Create a report to help us reproduce and fix the bug
+
+body:
+- type: markdown
+  attributes:
+    value: >
+      #### Before submitting a bug, please make sure the issue hasn't been already addressed by searching through [the existing and past issues](https://github.com/pytorch/vision/issues?q=is%3Aissue+sort%3Acreated-desc+).
+- type: textarea
+  attributes:
+    label: 🐛 Describe the bug
+    description: |
+      Please provide a clear and concise description of what the bug is.
+
+      If relevant, add a minimal example so that we can reproduce the error by running the code. It is very important for he snippet to be as succinct (minimal) as possible, so please take time to trim down any irrelevant code to help us debug efficiently. We are going to copy-paste your code and we expect to get the same result as you did: avoid any external data, and include the relevant imports, etc. For example:
+
+      ```python
+      # All necessary imports at the beginning
+      import torch
+      import torchvision
+      from torchvision.ops import nms
+
+      # A succinct reproducing example trimmed down to the essential parts:
+      N = 5
+      boxes = torch.rand(N, 4)  # Note: the bug is here, we should enforce that x1 < x2 and y1 < y2!
+      scores = torch.rand(N)
+      nms(boxes, scores, iou_threshold=.9)
+      ```
+
+      If the code is too long (hopefully, it isn't), feel free to put it in a public gist and link it in the issue: https://gist.github.com.
+
+      Please also paste or describe the results you observe instead of the expected results. If you observe an error, please paste the error message including the **full** traceback of the exception. It may be relevant to wrap error messages in ```` ```triple quotes blocks``` ````.
+    placeholder: |
+      A clear and concise description of what the bug is.
+
+      ```python
+      Sample code to reproduce the problem
+      ```
+
+      ```
+      The error message you got, with the full traceback.
+      ````
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Versions
+    description: |
+      Please run the following and paste the output below.
+      ```sh
+      wget https://github.com/raw/pytorch/pytorch/master/torch/utils/collect_env.py
+      # For security purposes, please check the contents of collect_env.py before running it.
+      python collect_env.py
+      ```
+  validations:
+    required: true
+- type: markdown
+  attributes:
+    value: >
+      Thanks for contributing 🎉!

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,5 @@
+blank_issues_enabled: true
+contact_links:
+  - name: Usage questions
+    url: https://discuss.pytorch.org/
+    about: Ask questions and discuss with other torchvision community members

.github/ISSUE_TEMPLATE/documentation.yml

@@ -0,0 +1,20 @@
+name: 📚 Documentation
+description: Report an issue related to https://pytorch.org/vision/stable/index.html
+
+body:
+- type: textarea
+  attributes:
+    label: 📚 The doc issue
+    description: >
+      A clear and concise description of what content in https://pytorch.org/vision/stable/index.html is an issue. If this has to do with the general https://pytorch.org website, please file an issue at https://github.com/pytorch/pytorch.github.io/issues/new/choose instead. If this has to do with https://pytorch.org/tutorials, please file an issue at https://github.com/pytorch/tutorials/issues/new.
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Suggest a potential alternative/fix
+    description: >
+      Tell us how we could improve the documentation in this regard.
+- type: markdown
+  attributes:
+    value: >
+      Thanks for contributing 🎉!

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -0,0 +1,32 @@
+name: 🚀 Feature request
+description: Submit a proposal/request for a new torchvision feature
+
+body:
+- type: textarea
+  attributes:
+    label: 🚀 The feature
+    description: >
+      A clear and concise description of the feature proposal
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Motivation, pitch
+    description: >
+      Please outline the motivation for the proposal. Is your feature request related to a specific problem? e.g., *"I'm working on X and would like Y to be possible"*. If this is related to another GitHub issue, please link here too.
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Alternatives
+    description: >
+      A description of any alternative solutions or features you've considered, if any.
+- type: textarea
+  attributes:
+    label: Additional context
+    description: >
+      Add any other context or screenshots about the feature request.
+- type: markdown
+  attributes:
+    value: >
+      Thanks for contributing 🎉!

docs/source/transforms.rst

@@ -24,7 +24,7 @@ number of channels, ``H`` and ``W`` are image height and width. A batch of
 Tensor Images is a tensor of ``(B, C, H, W)`` shape, where ``B`` is a number
 of images in the batch.
 
-The expected range of the values of a tensor image is implicitely defined by
+The expected range of the values of a tensor image is implicitly defined by
 the tensor dtype. Tensor images with a float dtype are expected to have
 values in ``[0, 1)``. Tensor images with an integer dtype are expected to
 have values in ``[0, MAX_DTYPE]`` where ``MAX_DTYPE`` is the largest value
@@ -35,7 +35,7 @@ images of a given batch, but they will produce different transformations
 across calls. For reproducible transformations across calls, you may use
 :ref:`functional transforms <functional_transforms>`.
 
-The following examples illustate the use of the available transforms:
+The following examples illustrate the use of the available transforms:
 
     * :ref:`sphx_glr_auto_examples_plot_transforms.py`
 

mypy.ini

@@ -20,10 +20,6 @@ ignore_errors=True
 
 ignore_errors = True
 
-[mypy-torchvision.models.quantization.*]
-
-ignore_errors = True
-
 [mypy-torchvision.ops.*]
 
 ignore_errors = True

torchvision/datasets/ucf101.py

@@ -14,7 +14,9 @@ class UCF101(VisionDataset):
     UCF101 is an action recognition video dataset.
     This dataset consider every video as a collection of video clips of fixed size, specified
     by ``frames_per_clip``, where the step in frames between each clip is given by
-    ``step_between_clips``.
+    ``step_between_clips``. The dataset itself can be downloaded from the dataset website;
+    annotations that ``annotation_path`` should be pointing to can be downloaded from `here
+    <https://www.crcv.ucf.edu/data/UCF101/UCF101TrainTestSplits-RecognitionTask.zip>`.
 
     To give an example, for 2 videos with 10 and 15 frames respectively, if ``frames_per_clip=5``
     and ``step_between_clips=5``, the dataset size will be (2 + 3) = 5, where the first two
@@ -26,7 +28,8 @@ class UCF101(VisionDataset):
 
     Args:
         root (string): Root directory of the UCF101 Dataset.
-        annotation_path (str): path to the folder containing the split files
+        annotation_path (str): path to the folder containing the split files;
+            see docstring above for download instructions of these files
         frames_per_clip (int): number of frames in a clip.
         step_between_clips (int, optional): number of frames between each clip.
         fold (int, optional): which fold to use. Should be between 1 and 3.

torchvision/io/__init__.py

@@ -1,4 +1,5 @@
 import torch
+from typing import Any, Dict, Iterator
 
 from ._video_opt import (
     Timebase,
@@ -33,13 +34,13 @@
 
 if _HAS_VIDEO_OPT:
 
-    def _has_video_opt():
+    def _has_video_opt() -> bool:
         return True
 
 
 else:
 
-    def _has_video_opt():
+    def _has_video_opt() -> bool:
         return False
 
 
@@ -99,7 +100,7 @@ class VideoReader:
             Currently available options include ``['video', 'audio']``
     """
 
-    def __init__(self, path, stream="video"):
+    def __init__(self, path: str, stream: str = "video") -> None:
         if not _has_video_opt():
             raise RuntimeError(
                 "Not compiled with video_reader support, "
@@ -109,7 +110,7 @@ def __init__(self, path, stream="video"):
             )
         self._c = torch.classes.torchvision.Video(path, stream)
 
-    def __next__(self):
+    def __next__(self) -> Dict[str, Any]:
         """Decodes and returns the next frame of the current stream.
         Frames are encoded as a dict with mandatory
         data and pts fields, where data is a tensor, and pts is a
@@ -126,10 +127,10 @@ def __next__(self):
             raise StopIteration
         return {"data": frame, "pts": pts}
 
-    def __iter__(self):
+    def __iter__(self) -> Iterator['VideoReader']:
         return self
 
-    def seek(self, time_s: float):
+    def seek(self, time_s: float) -> 'VideoReader':
         """Seek within current stream.
 
         Args:
@@ -144,15 +145,15 @@ def seek(self, time_s: float):
         self._c.seek(time_s)
         return self
 
-    def get_metadata(self):
+    def get_metadata(self) -> Dict[str, Any]:
         """Returns video metadata
 
         Returns:
             (dict): dictionary containing duration and frame rate for every stream
         """
         return self._c.get_metadata()
 
-    def set_current_stream(self, stream: str):
+    def set_current_stream(self, stream: str) -> bool:
         """Set current stream.
         Explicitly define the stream we are operating on.