This repository has been archived by the owner on Oct 13, 2021. It is now read-only.
Create Data #6
Open
Create Data #6
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Hi Gunjan, Thanks for your update. I just try using your code argoverse dataset.
I wonder how to create data train.trch by create_data.py?
I change the proto data path
I change the preprocess.py part to this one:
if info["include_roi"]:
roi_pts_flag = am.remove_non_roi_points(roi_pts, city_name) # remove non-driveable region
roi_pts_flag = np.array(roi_pts_flag, dtype=int)
roi_pts = np.array(roi_pts, dtype=int)
roi_pts = roi_pts[roi_pts_flag]
When I run pytorch train. I got this error:
Traceback (most recent call last):
File "pytorch/train.py", line 697, in
fire.Fire()
File "/home/joinet/anaconda3/lib/python3.7/site-packages/fire/core.py", line 138, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
File "/home/joinet/anaconda3/lib/python3.7/site-packages/fire/core.py", line 468, in _Fire
target=component.name)
File "/home/joinet/anaconda3/lib/python3.7/site-packages/fire/core.py", line 672, in _CallAndUpdateTrace
component = fn(*varargs, **kwargs)
File "pytorch/train.py", line 443, in train
raise e
File "pytorch/train.py", line 265, in train
example = next(data_iter)
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/_utils.py", line 394, in reraise
raise self.exc_type(msg)
ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/joinet/anaconda3/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/joinet/Semester_2/School/final/pointpillar_argoverse/second/pytorch/builder/input_reader_builder.py", line 42, in getitem
return self._dataset[idx]
File "/home/joinet/Semester_2/School/final/pointpillar_argoverse/second/data/dataset.py", line 162, in getitem
prep_func=self._prep_func)
File "/home/joinet/Semester_2/School/final/pointpillar_argoverse/second/data/preprocess.py", line 299, in _read_and_prep_v9
roi_pts = am.remove_ground_surface(roi_pts, city_name) # remove ground surface
File "/home/joinet/Semester_2/School/final/argoverse-api/argoverse/map_representation/map_api.py", line 303, in remove_ground_surface
is_ground_boolean_arr = self.get_ground_points_boolean(point_cloud, city_name)
File "/home/joinet/Semester_2/School/final/argoverse-api/argoverse/map_representation/map_api.py", line 354, in get_ground_points_boolean
ground_height_values = self.get_ground_height_at_xy(point_cloud, city_name)
File "/home/joinet/Semester_2/School/final/argoverse-api/argoverse/map_representation/map_api.py", line 378, in get_ground_height_at_xy
npyimage_coords = npyimage_to_city_se2.transform_point_cloud(city_coords)
File "/home/joinet/Semester_2/School/final/argoverse-api/argoverse/utils/se2.py", line 43, in transform_point_cloud
homogeneous_pts = np.hstack([point_cloud, np.ones((num_points, 1))])
File "<array_function internals>", line 6, in hstack
File "/home/joinet/anaconda3/lib/python3.7/site-packages/numpy/core/shape_base.py", line 345, in hstack
return _nx.concatenate(arrs, 1)
File "<array_function internals>", line 6, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 3 dimension(s) and the array at index 1 has 2 dimension(s)