[Docs] Add modelzoo statistics and polish docs (#201)

* add model stastics

* add model stastics and polish docs

* add model stastics and polish docs

* fix

* chmod +x stat.py

docs/conf.py

@@ -11,6 +11,7 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
 import os
+import subprocess
 import sys
 from m2r import MdInclude
 from recommonmark.transform import AutoStructify
@@ -87,7 +88,12 @@ html_theme = 'sphinx_rtd_theme'
 html_static_path = ['_static']
 
 
+def builder_inited_handler(app):
+    subprocess.run(['./stat.py'])
+
+
 def setup(app):
+    app.connect('builder-inited', builder_inited_handler)
     app.add_config_value('no_underscore_emphasis', False, 'env')
     app.add_config_value('m2r_parse_relative_links', False, 'env')
     app.add_config_value('m2r_anonymous_references', False, 'env')

docs/stat.py

+#!/usr/bin/env python
+import glob
+import re
+from os import path as osp
+
+url_prefix = 'https://github.com/open-mmlab/mmdetection3d/blob/master/'
+
+files = sorted(glob.glob('../configs/*/README.md'))
+
+stats = []
+titles = []
+num_ckpts = 0
+
+for f in files:
+    url = osp.dirname(f.replace('../', url_prefix))
+
+    with open(f, 'r') as content_file:
+        content = content_file.read()
+
+    title = content.split('\n')[0].replace('#', '')
+    titles.append(title)
+    ckpts = set(x.lower().strip()
+                for x in re.findall(r'https?://download.*\.pth', content)
+                if 'mmdetection3d' in x)
+    num_ckpts += len(ckpts)
+    statsmsg = f"""
+\t* [{title}]({url}) ({len(ckpts)} ckpts)
+"""
+    stats.append((title, ckpts, statsmsg))
+
+msglist = '\n'.join(x for _, _, x in stats)
+
+modelzoo = f"""
+\n## Model Zoo Statistics
+
+* Number of papers: {len(titles)}
+* Number of checkpoints: {num_ckpts}
+{msglist}
+"""
+
+with open('model_zoo.md', 'a') as f:
+    f.write(modelzoo)

mmdet3d/models/detectors/two_stage.py

@@ -7,8 +7,8 @@ class TwoStage3DDetector(Base3DDetector, TwoStageDetector):
     """Base class of two-stage 3D detector.
 
     It inherits original ``:class:TwoStageDetector`` and
-    ``:class:Base3DDetector``. This class could serve as a base class
-    for all two-stage 3D detectors.
+    ``:class:Base3DDetector``. This class could serve as a base class for all
+    two-stage 3D detectors.
     """
 
     def __init__(self, **kwargs):

mmdet3d/models/roi_heads/base_3droi_head.py

@@ -93,7 +93,7 @@ class Base3DRoIHead(nn.Module, metaclass=ABCMeta):
     def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
         """Test with augmentations.
 
-        If rescale is False, then returned bboxes and masks will fit the
-        scale of imgs[0].
+        If rescale is False, then returned bboxes and masks will fit the scale
+        of imgs[0].
         """
         pass

mmdet3d/ops/furthest_point_sample/furthest_point_sample.py

@@ -7,8 +7,8 @@ from . import furthest_point_sample_ext
 class FurthestPointSampling(Function):
     """Furthest Point Sampling.
 
-    Uses iterative furthest point sampling to select a set of features
-    whose corresponding points have the furthest distance.
+    Uses iterative furthest point sampling to select a set of features whose
+    corresponding points have the furthest distance.
     """
 
     @staticmethod

mmdet3d/ops/spconv/structure.py

@@ -5,9 +5,8 @@ import torch
 def scatter_nd(indices, updates, shape):
     """pytorch edition of tensorflow scatter_nd.
 
-    this function don't contain except handle code. so use this
-    carefully when indice repeats, don't support repeat add which is
-    supported in tensorflow.
+    this function don't contain except handle code. so use this carefully when
+    indice repeats, don't support repeat add which is supported in tensorflow.
     """
     ret = torch.zeros(*shape, dtype=updates.dtype, device=updates.device)
     ndim = indices.shape[-1]