Merge pull request #335 from Visual-Behavior/revert-332-torch_v2_unit…

…test_setup

Revert "Fix unit test & setup.py"

Dockerfile

@@ -4,10 +4,10 @@ FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04
 #FROM nvidia/cuda:11.6.0-cudnn8-devel-ubuntu20.04
 
 ARG py=3.9
-ARG pytorch=2.1.0.dev20230313+cu117
-ARG torchvision=0.15.0.dev20230313+cu117
-ARG torchaudio=2.0.0.dev20230313+cu117
-ARG pytorch_lightning=1.9.3
+ARG pytorch=1.13.1
+ARG torchvision=0.14.1
+ARG torchaudio=0.13.1
+ARG pytorch_lightning=1.9.0
 ARG pycyda=11.7
 
 ENV TZ=Europe/Paris
@@ -30,11 +30,8 @@ ENV HOME /workspace
 WORKDIR /workspace
 
 # Pytorch & pytorch litning
-#RUN conda install py pytorch-cuda=${pycuda} -c pytorch -c nvidia
-RUN pip install --pre torch==${pytorch} torchvision==${torchvision} torchaudio==${torchaudio} --index-url https://download.pytorch.org/whl/nightly/cu117
+RUN conda install pytorch==${pytorch} torchvision==${torchvision} torchaudio==${torchaudio} pytorch-cuda=${pycuda} -c pytorch -c nvidia
 RUN pip install pytorch_lightning==${pytorch_lightning}
 
-COPY requirements/requirements-torch2.1.txt /install/requirements-torch2.1.txt
-RUN pip install -r /install/requirements-torch2.1.txt
-COPY ./aloscene/utils /install/utils
-RUN cd /install/utils/rotated_iou/cuda_op/; python setup.py install --user
+COPY requirements-torch1.13.1.txt /install/requirements-torch1.13.1.txt
+RUN pip install -r /install/requirements-torch1.13.1.txt

README.md

@@ -78,17 +78,17 @@ training pipelines with **augmented tensors**.
 ### Docker install
 
 ```
-docker build -t aloception-oss:cuda-11.7-pytorch2.1.0-lightning1.9.3 .
+docker build -t aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0 .
 ```
 
 ```
-docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix aloception-oss:cuda-11.7-pytorch2.1.0-lightning1.9.3
+docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0
 ```
 
 Or without building the image
 
 ```
-docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix visualbehaviorofficial/aloception-oss:cuda-11.7-pytorch2.1.0-lightning1.9.3
+docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix visualbehaviorofficial/aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0
 ```
 
 

aloscene/depth.py

@@ -252,7 +252,7 @@ def as_points3d(
         target_names = tuple([n for n in self.names if n not in ("C", "H", "W")] + ["N", None])
         if points is None:
             y_points, x_points = torch.meshgrid(
-                torch.arange(self.H, device=self.device), torch.arange(self.W, device=self.device), indexing="ij"
+                torch.arange(self.H, device=self.device), torch.arange(self.W, device=self.device)
             )
             # Append batch & temporal dimensions
             for _ in range(len(target_shape[:-1])):

aloscene/tensors/spatial_augmented_tensor.py

@@ -526,7 +526,7 @@ def _resize(self, size, interpolation=InterpolationMode.BILINEAR, **kwargs):
         if ("N" in self.names and self.size("N") == 0) or ("C" in self.names and self.size("C") == 0):
             shapes = list(self.shape)[:-2] + [h, w]
             return self.rename(None).view(shapes).reset_names()
-        return F.resize(self.rename(None), (h, w), interpolation=interpolation, antialias=True).reset_names()
+        return F.resize(self.rename(None), (h, w), interpolation=interpolation).reset_names()
 
     def _rotate(self, angle, center=None,**kwargs):
         """Rotate SpatialAugmentedTensor, but not its labels
@@ -548,7 +548,7 @@ def _rotate(self, angle, center=None,**kwargs):
         ), "rotation is not possible on an empty tensor"
         return F.rotate(self.rename(None), angle,center=center).reset_names()
 
-    def _crop(self, H_crop: tuple, W_crop: tuple, warn_non_integer=True, **kwargs):
+    def _crop(self, H_crop: tuple, W_crop: tuple, **kwargs):
         """Crop the SpatialAugmentedTensor
 
         Parameters
@@ -557,16 +557,14 @@ def _crop(self, H_crop: tuple, W_crop: tuple, warn_non_integer=True, **kwargs):
             (start, end) between 0 and 1
         W_crop: tuple
             (start, end) between 0 and 1
-        warn_non_integer: bool
-            If True, warn if the crop is not integer
 
         Returns
         -------
         cropped sa_tensor: aloscene.SpatialAugmentedTensor
             cropped SpatialAugmentedTensor
         """
 
-        H_crop, W_crop = self._relative_to_absolute_hs_ws(H_crop, W_crop, assert_integer=False, warn_non_integer=warn_non_integer)
+        H_crop, W_crop = self._relative_to_absolute_hs_ws(H_crop, W_crop, assert_integer=False, warn_non_integer=True)
         hmin, hmax = H_crop
         wmin, wmax = W_crop
         slices = self.get_slices({"H": slice(hmin, hmax), "W": slice(wmin, wmax)})

aloscene/utils/rotated_iou/cuda_op/sort_vertices.egg-info/PKG-INFO

@@ -1,10 +1,10 @@
-Metadata-Version: 2.1
+Metadata-Version: 1.0
 Name: sort-vertices
 Version: 0.0.0
 Summary: UNKNOWN
 Home-page: UNKNOWN
+Author: UNKNOWN
+Author-email: UNKNOWN
 License: UNKNOWN
+Description: UNKNOWN
 Platform: UNKNOWN
-
-UNKNOWN
-

setup.py

@@ -3,39 +3,32 @@
 setup(
     name='aloception',
     author='Visual Behavior',
-    version='0.5.1',
+    version='0.3.0',
     description='Aloception is a set of package for computer vision: aloscene, alodataset, alonet.',
     packages=find_packages(include=['aloscene', 'alodataset', 'alonet']),
     url='https://visualbehavior.ai/',
     download_url='https://github.com/Visual-Behavior/aloception-oss',
     install_requires=[
-        'pycocotools==2.0.2',
-        'PyYAML==5.4.1',
-        'chardet==4.0.0',
-        'idna==2.10',
-
-        'scipy==1.10.0',
-
-        'more_itertools==8.8.0',
-        'requests==2.25.1',
-        'opencv-python==4.7.0.68',
-
-        'python-dateutil==2.8.2',
-        'urllib3==1.26.6',
-
-        'protobuf==4.21.12',
-        'wandb==0.13.9',
-
+        'matplotlib==3.5.3',
+        'more-itertools==8.8.0', # required for alodataset waymo
+        'onnx==1.12.0',
+        'onnx_graphsurgeon==0.0.1.dev5',
+        'onnxsim==0.4.8',
+        'opencv-python==4.5.3.56'
+        'Pillow==9.2.0',
+        'pycocotools==2.0.2',    # required for alodataset coco
+        'pytorch_lightning==1.4.1',
+        'pytorch_quantization==0.0.1.dev5',
+        'Requests==2.28.1',
+        'scipy==1.4.1',          # required for alonet/detr/matcher
+        'setuptools==63.4.1',
+        'tensorflow==2.10.0',    # required for alodataset/prepare/waymo_converter
+        'tensorrt==0.0.1.dev5',
+        'torchvision==0.13.1',
         'tqdm==4.62.3',
-        'captum==0.4.0',
-
-        'setuptools==59.5.0',
-
-        'numpy==1.23.5',
-
-        'pytest==7.2.2',
-        'Image==1.5.33'
-        ],
+        'ts==0.5.1',
+        'wandb==0.12.2',
+        'waymo_open_dataset==1.0.1'],
     setup_requires=['numpy', 'torch', 'nvidia-pyindex', 'pycuda'],
     license_files=['LICENSE'],
     keywords=['artificial intelligence', 'computer vision'],

unittest/test_augmented_tensor.py

@@ -64,8 +64,3 @@ def test_batch_list_intersection_unmergeable_child():
     assert len(f.flow) == 2
     assert f.flow[0].shape == (2, 10, 10)
     assert f.flow[1] is None
-
-if __name__ == "__main__":
-    test_batch_list_intersection_property()
-    test_batch_list_intersection_mergeable_child()
-    test_batch_list_intersection_unmergeable_child()

unittest/test_oriented_boxes_2d.py

@@ -3,7 +3,7 @@
 import aloscene
 from aloscene import OrientedBoxes2D
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+device = torch.device("cpu")
 
 
 def tensor_equal(tensor1, tensor2, threshold=1e-4):

unittest/test_points2d.py

@@ -9,15 +9,12 @@ def test_crop_abs():
     image = np.zeros((3, 843, 1500))
     corners = [[298, 105], [1250, 105], [298, 705], [1250, 705]]
     frame = aloscene.Frame(image)
-    labels = aloscene.Labels([0, 1, 2, 3], labels_names=["corners0", "corners1", "corners2", "corners3"])
+    labels = aloscene.Labels([0, 0, 0, 0], labels_names=["corners"])
     corners = aloscene.Points2D(
         corners, points_format="xy", frame_size=(frame.H, frame.W), absolute=True, labels=labels
     )
-
     frame.append_points2d(corners)
-
-    frame = frame.crop(H_crop=(0.0, 0.5), W_crop=(0.0, 0.5), warn_non_integer=False)
-
+    frame = frame.crop(H_crop=(0.0, 0.5), W_crop=(0.0, 0.5))
     assert torch.allclose(frame.points2d[0].as_tensor(), corners[0].as_tensor())
     assert np.allclose(frame.points2d.frame_size[0], frame.HW[0])
     assert np.allclose(frame.points2d.frame_size[1], frame.HW[1])

unittest/test_projections.py

@@ -16,7 +16,8 @@ def _test_disp_depth_points3d(depth, height, width, resize=True):
         )
 
         d = depth.resize((height * 2, width * 2))
-        v = depth.resize((height * 2, width * 2)).as_disp()#.resize((height, width)).as_depth()
+
+        v = depth.resize((height * 2, width * 2)).as_disp().resize((height, width)).as_depth()
 
         assert torch.allclose(
             depth.as_tensor(),
@@ -122,5 +123,5 @@ def test_disp_depth_points3d_projection4():
 
 if __name__ == "__main__":
     test_disp_depth_points3d_projection1()
-    #test_disp_depth_points3d_projection2()
-    #test_disp_depth_points3d_projection4()
+    test_disp_depth_points3d_projection2()
+    test_disp_depth_points3d_projection4()