anhquancao commited on
Commit
b5be88d
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1 Parent(s): e4a653e

downsample output

Browse files
__pycache__/fusion.cpython-37.pyc DELETED
Binary file (14.9 kB)
 
app.py CHANGED
@@ -46,18 +46,17 @@ def predict(img):
46
 
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  pred = model(batch).squeeze()
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  # print(pred.shape)
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- # pred = majority_pooling(pred, k_size=2)
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- fig = draw(pred, batch['fov_mask_1'])
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52
 
53
  return fig
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- # The output is <b>downsampled by 2</b> to be able to be rendered in browsers.
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57
  description = """
58
  MonoScene Demo on SemanticKITTI Validation Set (Sequence 08), which uses the <b>camera parameters of Sequence 08</b>.
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  Due to the <b>CPU-only</b> inference, it might take up to 20s to predict a scene. \n
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- <b>Darker</b> colors represent the <b>scenery outside the Field of View</b>, i.e. not visible on the image.
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  <center>
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  <a href="https://cv-rits.github.io/MonoScene/">
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  <img style="display:inline" alt="Project page" src="https://img.shields.io/badge/Project%20Page-MonoScene-red">
@@ -74,7 +73,9 @@ article="""
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  """
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  examples = [
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- 'images/08/000010.jpg',
 
 
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  'images/08/000085.jpg',
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  'images/08/000290.jpg',
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  'images/08/000465.jpg',
@@ -83,10 +84,10 @@ examples = [
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  'images/08/001380.jpg',
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  'images/08/001530.jpg',
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  'images/08/002360.jpg',
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- 'images/08/002505.jpg',
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  'images/08/004059.jpg',
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  'images/08/003149.jpg',
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  'images/08/001446.jpg',
 
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  'images/08/001122.jpg',
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  'images/08/003533.jpg',
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  'images/08/003365.jpg',
 
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  pred = model(batch).squeeze()
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  # print(pred.shape)
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+ pred = majority_pooling(pred, k_size=2)
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+ fig = draw(pred, batch['fov_mask_2'])
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  return fig
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  description = """
57
  MonoScene Demo on SemanticKITTI Validation Set (Sequence 08), which uses the <b>camera parameters of Sequence 08</b>.
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  Due to the <b>CPU-only</b> inference, it might take up to 20s to predict a scene. \n
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+ The output is <b>downsampled by 2</b> for faster rendering. <b>Darker</b> colors represent the <b>scenery outside the Field of View</b>, i.e. not visible on the image.
60
  <center>
61
  <a href="https://cv-rits.github.io/MonoScene/">
62
  <img style="display:inline" alt="Project page" src="https://img.shields.io/badge/Project%20Page-MonoScene-red">
 
73
  """
74
 
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  examples = [
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+ 'images/08/001385.jpg',
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+ 'images/08/000295.jpg',
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+ 'images/08/002505.jpg',
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  'images/08/000085.jpg',
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  'images/08/000290.jpg',
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  'images/08/000465.jpg',
 
84
  'images/08/001380.jpg',
85
  'images/08/001530.jpg',
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  'images/08/002360.jpg',
 
87
  'images/08/004059.jpg',
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  'images/08/003149.jpg',
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  'images/08/001446.jpg',
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+ 'images/08/000010.jpg',
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  'images/08/001122.jpg',
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  'images/08/003533.jpg',
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  'images/08/003365.jpg',
helpers.py CHANGED
@@ -188,7 +188,7 @@ def draw(
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  fov_mask,
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  # img_size,
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  # f,
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- voxel_size=0.2,
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  # d=7, # 7m - determine the size of the mesh representing the camera
193
  ):
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  fov_mask,
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  # img_size,
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  # f,
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+ voxel_size=0.4,
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  # d=7, # 7m - determine the size of the mesh representing the camera
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  ):
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images/08/000295.jpg ADDED
images/08/001385.jpg ADDED
monoscene/__pycache__/CRP3D.cpython-37.pyc DELETED
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monoscene/__pycache__/DDR.cpython-37.pyc DELETED
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monoscene/__pycache__/__init__.cpython-37.pyc DELETED
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monoscene/__pycache__/config.cpython-37.pyc DELETED
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monoscene/__pycache__/flosp.cpython-37.pyc DELETED
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monoscene/__pycache__/modules.cpython-37.pyc DELETED
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monoscene/__pycache__/monoscene.cpython-37.pyc DELETED
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monoscene/__pycache__/monoscene_model.cpython-37.pyc DELETED
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monoscene/__pycache__/unet2d.cpython-37.pyc DELETED
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monoscene/__pycache__/unet3d_kitti.cpython-37.pyc DELETED
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monoscene/__pycache__/unet3d_nyu.cpython-37.pyc DELETED
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monoscene/monoscene.py CHANGED
@@ -96,15 +96,15 @@ class MonoScene(pl.LightningModule):
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  if x3d is None:
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  x3d = self.projects[str(scale_2d)](
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  x_rgb["1_" + str(scale_2d)][i],
99
- torch.div(projected_pix, scale_2d, rounding_mode='floor'),
100
- # projected_pix // scale_2d,
101
  fov_mask,
102
  )
103
  else:
104
  x3d += self.projects[str(scale_2d)](
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  x_rgb["1_" + str(scale_2d)][i],
106
- torch.div(projected_pix, scale_2d, rounding_mode='floor'),
107
- # projected_pix // scale_2d,
108
  fov_mask,
109
  )
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  x3ds.append(x3d)
 
96
  if x3d is None:
97
  x3d = self.projects[str(scale_2d)](
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  x_rgb["1_" + str(scale_2d)][i],
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+ # torch.div(projected_pix, scale_2d, rounding_mode='floor'),
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+ projected_pix // scale_2d,
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  fov_mask,
102
  )
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  else:
104
  x3d += self.projects[str(scale_2d)](
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  x_rgb["1_" + str(scale_2d)][i],
106
+ # torch.div(projected_pix, scale_2d, rounding_mode='floor'),
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+ projected_pix // scale_2d,
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  fov_mask,
109
  )
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  x3ds.append(x3d)