aicps / roadscene2vec Goto Github PK
View Code? Open in Web Editor NEWA Tool for Extracting and Embedding Road Scene-Graphs
License: MIT License
A Tool for Extracting and Embedding Road Scene-Graphs
License: MIT License
When I run use_case_1.py, the following error appears, what is the problem?
/home/lcx/anaconda3/envs/av3/bin/python /home/lcx/PycharmProjects/roadscene2vec-main/examples/use_case_1.py
0it [00:00, ?it/s]
0it [00:00, ?it/s]
Hi, I have downloaded your newly updated folder 'use_case_data', but I didn't find the 'sequence_classification_example_model.pt'.
I would like to know whether the folder 'use_case_data' of the previous version can still be used.
roadscene2vec/learning/util/trainer.py", line 40, in init
if self.config.training_configuration["seed"] != None:
AttributeError: 'configuration' object has no attribute 'training_configuration'
pytorch: 1.10.0
torchvision: 0.11.1
cudatoolkit: 11.3.1
Hello, thank you for providing excellent work about scene-graph! I am interested in your work, and I‘d like to ask that, could you provide the raw data in google drive? The source about IEEE dataport can not be downloaded free. It is more helpful to promote works in this field. Thank you again!
I reported an error when trying to run the first use case. Does this problem exist in a specific version of networkx?
pytorch==1.10.0
cudatoolkit==11.3.1
networkx==2.6.3
The following is error infomation:
(av) ranyabing@ranyabing:~/roadscene2vec/examples$ python use_case_1.py
100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:02<00:00, 2.45s/it]
0%| | 0/1 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/ranyabing/roadscene2vec/examples/use_case_1.py", line 35, in
visualize(scenegraph_extraction_config) #visualize extracted scenegraphs
File "/home/ranyabing/roadscene2vec/roadscene2vec/util/visualizer.py", line 172, in visualize
visualize_real_image(extraction_config)
File "/home/ranyabing/roadscene2vec/roadscene2vec/util/visualizer.py", line 192, in visualize_real_image
draw(extractor, sequence[frame], bbox, bev, sg, save_path='output.png')
File "/home/ranyabing/roadscene2vec/roadscene2vec/util/visualizer.py", line 131, in draw
sg_img = draw_scenegraph_pydot(sg)
File "/home/ranyabing/roadscene2vec/roadscene2vec/util/visualizer.py", line 105, in draw_scenegraph_pydot
A = nx_pydot.to_pydot(sg)
File "/home/ranyabing/anaconda3/envs/av/lib/python3.9/site-packages/networkx/drawing/nx_pydot.py", line 263, in to_pydot
raise ValueError(
ValueError: Node names and attributes should not contain ":" unless they are quoted with "". For example the string 'attribute:data1' should be written as '"attribute:data1"'. Please refer pydot/pydot#258
Dear editor,
Thank you for your brilliant work. According to section 3.1 of your paper, your implement an annotation tool with a graphical user interface (GUI). However, I can not find the corresponding code in this project. Could you provide more information that how to use the annotation tool?
Looking forward to your reply.
Hi!Thank you for your excellent work. In terms of use case 2, how can I get the pretrained model? I didn't find '/pretrained_models/mrgcn_sequence_classification_model.pt'.
Hi, I found the pretrained model that you provide is not right. I use Netron to visualize the pretrained model, model is incomplete, the FastRGCNConv module is lost. And I found the def save_model(self) in trainer.py is wrong, the function can not save the whole model weight, could you please fix it, thank you.
Hello,
I tried running the first use_case after performing all the installation steps as mentioned in your README. I faced the following error:
model_final_f10217.pkl: 178MB [00:18, 9.71MB/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:03<00:00, 3.04s/it]
0%| | 0/1 [00:01<?, ?it/s]
Traceback (most recent call last):
File "/home/bourne/anaconda3/envs/av/lib/python3.9/site-packages/pydot.py", line 1923, in create
stdout_data, stderr_data, process = call_graphviz(
File "/home/bourne/anaconda3/envs/av/lib/python3.9/site-packages/pydot.py", line 132, in call_graphviz
process = subprocess.Popen(
File "/home/bourne/anaconda3/envs/av/lib/python3.9/subprocess.py", line 951, in __init__
self._execute_child(args, executable, preexec_fn, close_fds,
File "/home/bourne/anaconda3/envs/av/lib/python3.9/subprocess.py", line 1821, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
FileNotFoundError: [Errno 2] No such file or directory: 'dot'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/bourne/dlr/git_repos/roadscene2vec/examples/use_case_1.py", line 33, in <module>
visualize(scenegraph_extraction_config) #visualize extracted scenegraphs
File "/home/bourne/dlr/git_repos/roadscene2vec/roadscene2vec/util/visualizer.py", line 168, in visualize
visualize_real_image(extraction_config)
File "/home/bourne/dlr/git_repos/roadscene2vec/roadscene2vec/util/visualizer.py", line 188, in visualize_real_image
draw(extractor, sequence[frame], bbox, bev, sg, save_path='output.png')
File "/home/bourne/dlr/git_repos/roadscene2vec/roadscene2vec/util/visualizer.py", line 127, in draw
sg_img = draw_scenegraph_pydot(sg)
File "/home/bourne/dlr/git_repos/roadscene2vec/roadscene2vec/util/visualizer.py", line 103, in draw_scenegraph_pydot
img = A.create_png()
File "/home/bourne/anaconda3/envs/av/lib/python3.9/site-packages/pydot.py", line 1733, in new_method
return self.create(
File "/home/bourne/anaconda3/envs/av/lib/python3.9/site-packages/pydot.py", line 1933, in create
raise OSError(*args)
FileNotFoundError: [Errno 2] "dot" not found in path.
This was resolved by installing graphviz conda install -c anaconda graphviz
. However I failed to find any place in the documentation where this was explicitly mentioned as a requirement, which it should be.
I can not find it in the HDD dataset
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