[fbsync] Doc revamp for optical flow models (#5895)

Summary:
* Doc revamp for optical flow models

* Some more

Reviewed By: NicolasHug

Differential Revision: D36760919

fbshipit-source-id: b43d45ec9fe9d3a1663a341ef6dec746c7bb1ace

Author: YosuaMichael

docs/source/conf.py

@@ -347,6 +347,7 @@ def inject_weight_metadata(app, what, name, obj, options, lines):
             metrics = meta.pop("_metrics")
             for dataset, dataset_metrics in metrics.items():
                 for metric_name, metric_value in dataset_metrics.items():
+                    metric_name = metric_name.replace("_", "-")
                     table.append((f"{metric_name} (on {dataset})", str(metric_value)))
 
             for k, v in meta.items():

docs/source/models/raft.rst

@@ -0,0 +1,25 @@
+RAFT
+====
+
+.. currentmodule:: torchvision.models.optical_flow
+
+The RAFT model is based on the `RAFT: Recurrent All-Pairs Field Transforms for
+Optical Flow <https://arxiv.org/abs/2003.12039>`__ paper.
+
+
+Model builders
+--------------
+
+The following model builders can be used to instantiate a RAFT model, with or
+without pre-trained weights. All the model builders internally rely on the
+``torchvision.models.optical_flow.RAFT`` base class. Please refer to the `source
+code
+<https://github.com/pytorch/vision/blob/main/torchvision/models/optical_flow/raft.py>`_ for
+more details about this class.
+
+.. autosummary::
+    :toctree: generated/
+    :template: function.rst
+
+    raft_large
+    raft_small

docs/source/models_new.rst

@@ -376,6 +376,7 @@ Box MAPs are reported on COCO val2017:
 
 .. include:: generated/detection_table.rst
 
+
 Instance Segmentation
 ---------------------
 
@@ -481,6 +482,18 @@ Accuracies are reported on Kinetics-400 using single crops for clip length 16:
 
 .. include:: generated/video_table.rst
 
+Optical Flow
+============
+
+.. currentmodule:: torchvision.models.optical_flow
+
+The following Optical Flow models are available, with or without pre-trained
+
+.. toctree::
+   :maxdepth: 1
+
+   models/raft
+
 Using models from Hub
 =====================
 

torchvision/models/optical_flow/raft.py

@@ -517,6 +517,19 @@ def forward(self, image1, image2, num_flow_updates: int = 12):
 
 
 class Raft_Large_Weights(WeightsEnum):
+    """The metrics reported here are as follows.
+
+    ``epe`` is the "end-point-error" and indicates how far (in pixels) the
+    predicted flow is from its true value. This is averaged over all pixels
+    of all images. ``per_image_epe`` is similar, but the average is different:
+    the epe is first computed on each image independently, and then averaged
+    over all images. This corresponds to "Fl-epe" (sometimes written "F1-epe")
+    in the original paper, and it's only used on Kitti. ``fl-all`` is also a
+    Kitti-specific metric, defined by the author of the dataset and used for the
+    Kitti leaderboard. It corresponds to the average of pixels whose epe is
+    either <3px, or <5% of flow's 2-norm.
+    """
+
     C_T_V1 = Weights(
         # Weights ported from https://github.com/princeton-vl/RAFT
         url="https://download.pytorch.org/models/raft_large_C_T_V1-22a6c225.pth",
@@ -530,7 +543,9 @@ class Raft_Large_Weights(WeightsEnum):
                 "Sintel-Train-Finalpass": {"epe": 2.7894},
                 "Kitti-Train": {"per_image_epe": 5.0172, "fl_all": 17.4506},
             },
-            "_docs": """These weights were ported from the original paper. They are trained on Chairs + Things.""",
+            "_docs": """These weights were ported from the original paper. They
+            are trained on :class:`~torchvision.datasets.FlyingChairs` +
+            :class:`~torchvision.datasets.FlyingThings3D`.""",
         },
     )
 
@@ -546,7 +561,9 @@ class Raft_Large_Weights(WeightsEnum):
                 "Sintel-Train-Finalpass": {"epe": 2.7161},
                 "Kitti-Train": {"per_image_epe": 4.5118, "fl_all": 16.0679},
             },
-            "_docs": """These weights were trained from scratch on Chairs + Things.""",
+            "_docs": """These weights were trained from scratch on
+            :class:`~torchvision.datasets.FlyingChairs` +
+            :class:`~torchvision.datasets.FlyingThings3D`.""",
         },
     )
 
@@ -563,8 +580,14 @@ class Raft_Large_Weights(WeightsEnum):
                 "Sintel-Test-Finalpass": {"epe": 3.18},
             },
             "_docs": """
-                These weights were ported from the original paper. They are trained on Chairs + Things and fine-tuned on
-                Sintel (C+T+S+K+H).
+                These weights were ported from the original paper. They are
+                trained on :class:`~torchvision.datasets.FlyingChairs` +
+                :class:`~torchvision.datasets.FlyingThings3D` and fine-tuned on
+                Sintel. The Sintel fine-tuning step is a combination of
+                :class:`~torchvision.datasets.Sintel`,
+                :class:`~torchvision.datasets.KittiFlow`,
+                :class:`~torchvision.datasets.HD1K`, and
+                :class:`~torchvision.datasets.FlyingThings3D` (clean pass).
             """,
         },
     )
@@ -581,7 +604,14 @@ class Raft_Large_Weights(WeightsEnum):
                 "Sintel-Test-Finalpass": {"epe": 3.067},
             },
             "_docs": """
-                These weights were trained from scratch on Chairs + Things and fine-tuned on Sintel (C+T+S+K+H).
+                These weights were trained from scratch. They are
+                pre-trained on :class:`~torchvision.datasets.FlyingChairs` +
+                :class:`~torchvision.datasets.FlyingThings3D` and then
+                fine-tuned on Sintel. The Sintel fine-tuning step is a
+                combination of :class:`~torchvision.datasets.Sintel`,
+                :class:`~torchvision.datasets.KittiFlow`,
+                :class:`~torchvision.datasets.HD1K`, and
+                :class:`~torchvision.datasets.FlyingThings3D` (clean pass).
             """,
         },
     )
@@ -598,8 +628,12 @@ class Raft_Large_Weights(WeightsEnum):
                 "Kitti-Test": {"fl_all": 5.10},
             },
             "_docs": """
-                These weights were ported from the original paper. They are trained on Chairs + Things, fine-tuned on
-                Sintel and then on Kitti.
+                These weights were ported from the original paper. They are
+                pre-trained on :class:`~torchvision.datasets.FlyingChairs` +
+                :class:`~torchvision.datasets.FlyingThings3D`,
+                fine-tuned on Sintel, and then fine-tuned on
+                :class:`~torchvision.datasets.KittiFlow`. The Sintel fine-tuning
+                step was described above.
             """,
         },
     )
@@ -615,7 +649,12 @@ class Raft_Large_Weights(WeightsEnum):
                 "Kitti-Test": {"fl_all": 5.19},
             },
             "_docs": """
-                These weights were trained from scratch on Chairs + Things, fine-tuned on Sintel and then on Kitti.
+                These weights were trained from scratch. They are
+                pre-trained on :class:`~torchvision.datasets.FlyingChairs` +
+                :class:`~torchvision.datasets.FlyingThings3D`,
+                fine-tuned on Sintel, and then fine-tuned on
+                :class:`~torchvision.datasets.KittiFlow`. The Sintel fine-tuning
+                step was described above.
             """,
         },
     )
@@ -624,6 +663,19 @@ class Raft_Large_Weights(WeightsEnum):
 
 
 class Raft_Small_Weights(WeightsEnum):
+    """The metrics reported here are as follows.
+
+    ``epe`` is the "end-point-error" and indicates how far (in pixels) the
+    predicted flow is from its true value. This is averaged over all pixels
+    of all images. ``per_image_epe`` is similar, but the average is different:
+    the epe is first computed on each image independently, and then averaged
+    over all images. This corresponds to "Fl-epe" (sometimes written "F1-epe")
+    in the original paper, and it's only used on Kitti. ``fl-all`` is also a
+    Kitti-specific metric, defined by the author of the dataset and used for the
+    Kitti leaderboard. It corresponds to the average of pixels whose epe is
+    either <3px, or <5% of flow's 2-norm.
+    """
+
     C_T_V1 = Weights(
         # Weights ported from https://github.com/princeton-vl/RAFT
         url="https://download.pytorch.org/models/raft_small_C_T_V1-ad48884c.pth",
@@ -637,7 +689,9 @@ class Raft_Small_Weights(WeightsEnum):
                 "Sintel-Train-Finalpass": {"epe": 3.2790},
                 "Kitti-Train": {"per_image_epe": 7.6557, "fl_all": 25.2801},
             },
-            "_docs": """These weights were ported from the original paper. They are trained on Chairs + Things.""",
+            "_docs": """These weights were ported from the original paper. They
+            are trained on :class:`~torchvision.datasets.FlyingChairs` +
+            :class:`~torchvision.datasets.FlyingThings3D`.""",
         },
     )
     C_T_V2 = Weights(
@@ -652,7 +706,9 @@ class Raft_Small_Weights(WeightsEnum):
                 "Sintel-Train-Finalpass": {"epe": 3.2831},
                 "Kitti-Train": {"per_image_epe": 7.5978, "fl_all": 25.2369},
             },
-            "_docs": """These weights were trained from scratch on Chairs + Things.""",
+            "_docs": """These weights were trained from scratch on
+            :class:`~torchvision.datasets.FlyingChairs` +
+            :class:`~torchvision.datasets.FlyingThings3D`.""",
         },
     )
 
@@ -750,13 +806,19 @@ def raft_large(*, weights: Optional[Raft_Large_Weights] = None, progress=True, *
     Please see the example below for a tutorial on how to use this model.
 
     Args:
-        weights(Raft_Large_weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
-        kwargs (dict): Parameters that will be passed to the :class:`~torchvision.models.optical_flow.RAFT` class
-            to override any default.
-
-    Returns:
-        RAFT: The model.
+        weights(:class:`~torchvision.models.optical_flow.Raft_Large_Weights`, optional): The
+            pretrained weights to use. See
+            :class:`~torchvision.models.optical_flow.Raft_Large_Weights`
+            below for more details, and possible values. By default, no
+            pre-trained weights are used.
+        progress (bool): If True, displays a progress bar of the download to stderr. Default is True.
+        **kwargs: parameters passed to the ``torchvision.models.optical_flow.RAFT``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/optical_flow/raft.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.optical_flow.Raft_Large_Weights
+        :members:
     """
 
     weights = Raft_Large_Weights.verify(weights)
@@ -794,19 +856,24 @@ def raft_large(*, weights: Optional[Raft_Large_Weights] = None, progress=True, *
 @handle_legacy_interface(weights=("pretrained", Raft_Small_Weights.C_T_V2))
 def raft_small(*, weights: Optional[Raft_Small_Weights] = None, progress=True, **kwargs) -> RAFT:
     """RAFT "small" model from
-    `RAFT: Recurrent All Pairs Field Transforms for Optical Flow <https://arxiv.org/abs/2003.12039>`_.
+    `RAFT: Recurrent All Pairs Field Transforms for Optical Flow <https://arxiv.org/abs/2003.12039>`__.
 
     Please see the example below for a tutorial on how to use this model.
 
     Args:
-        weights(Raft_Small_weights, optional): The pretrained weights for the model
-        progress (bool): If True, displays a progress bar of the download to stderr
-        kwargs (dict): Parameters that will be passed to the :class:`~torchvision.models.optical_flow.RAFT` class
-            to override any default.
-
-    Returns:
-        RAFT: The model.
-
+        weights(:class:`~torchvision.models.optical_flow.Raft_Small_Weights`, optional): The
+            pretrained weights to use. See
+            :class:`~torchvision.models.optical_flow.Raft_Small_Weights`
+            below for more details, and possible values. By default, no
+            pre-trained weights are used.
+        progress (bool): If True, displays a progress bar of the download to stderr. Default is True.
+        **kwargs: parameters passed to the ``torchvision.models.optical_flow.RAFT``
+            base class. Please refer to the `source code
+            <https://github.com/pytorch/vision/blob/main/torchvision/models/optical_flow/raft.py>`_
+            for more details about this class.
+
+    .. autoclass:: torchvision.models.optical_flow.Raft_Small_Weights
+        :members:
     """
     weights = Raft_Small_Weights.verify(weights)