uzh-rpg / dagr Goto Github PK
View Code? Open in Web Editor NEWCode for the paper "Low Latency Automotive Vision with Event Cameras", published in Nature
License: GNU General Public License v3.0
dagr's People
Contributors
Stargazers
Watchers
Forkers
biomechatronics001 wencan-huang xiaojake ca-uavs whu-lyh bluet-neurorobotics kjeziorek yyzhihuishu lyxlyxlyv ansonyan1989 fuwujiaxx xiaofeifei-1 jiyuzhe cloudenginehub junyang0412 mgcxr andreasaziegler jingxuanyang dr-gezhedagr's Issues
About the training procedure
Hi!
Great work! It's a strong demonstration of the further application of Event Camera.
The code for the mentioned part in the paper is not included in this repository. Looking forward for the training code.
data fragment and checkpoint download links are invalid
In the RUN example PART, the code below can't run successfully.I find the Links are invalid, please update it,thx.
#! /usr/bin/env bash
DAGR_DIR=$(pwd)
DATA_DIR=$DAGR_DIR/data
mkdir $DATA_DIR
wget https://download.ifi.uzh.ch/rpg/dagr/data/dagr_s_50.pth -O $DATA_DIR/dagr_s_50.pth
wget https://download.ifi.uzh.ch/rpg/dagr/data/DSEC_fragment.zip -O $DATA_DIR/DSEC_fragment.zip
unzip $DATA_DIR/DSEC_fragment.zip -d $DATA_DIR
rm -rf $DATA_DIR/DSEC_fragment.zip
How about the training code?
Thank you for your excellent work.
Maybe you can open source the training code for my reference?
Thanks a lot !!!!
Questions about the result.
It's a great job.
But I was a little confused about the code. I use your checkpoint. Why the mAP is lower than the results in your paper?
Is the mAP in your paper mAP[0.5:0.95:0.05] or mAP50?
THANKS!
:)
Cannot import name 'extract_image_by_index' from 'dsec_det.io'
It's a great job. But I got an error when running scripts/visualize_detections.py. I don't know if the code version needs to be updated.
Traceback (most recent call last):
File "scripts/visualize_detections.py", line 8, in <module>
from dsec_det.io import extract_from_h5_by_timewindow, extract_image_by_index, load_start_and_end_time
ImportError: cannot import name 'extract_image_by_index' from 'dsec_det.io' (/workspace/jb/dagr/libs/dsec-det/src/dsec_det/io.py)
RuntimeError: CUDA error: CUBLAS_STATUS_NOT_SUPPORTED when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`
I got an error when running run_test_interframe.py according to README.md.
How to solve it?
/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/TensorShape.cpp:2228.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
Testing curious-oath-7: 0%| | 0/19 [00:00<?, ?it/s]
Traceback (most recent call last):
File "scripts/run_test_interframe.py", line 85, in <module>
metrics, detections_one_offset = run_test_with_visualization(test_loader, ema.ema, dataset=args.dataset, name=wandb.run.name, compile_detections=True,
File "/home/apollon-22/dagr/dagr/src/dagr/utils/testing.py", line 33, in run_test_with_visualization
detections, targets = model(data.clone())
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/apollon-22/dagr/dagr/src/dagr/model/networks/dagr.py", line 91, in forward
outputs = YOLOX.forward(self, x)
File "/home/apollon-22/dagr/dagr/libs/YOLOX/yolox/models/yolox.py", line 30, in forward
fpn_outs = self.backbone(x)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/apollon-22/dagr/dagr/src/dagr/model/networks/net.py", line 108, in forward
image_feat, image_outputs = self.net(data.image)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/apollon-22/dagr/dagr/src/dagr/model/networks/net_img.py", line 125, in forward
self.module(x)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torchvision/models/resnet.py", line 283, in forward
return self._forward_impl(x)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torchvision/models/resnet.py", line 278, in _forward_impl
x = self.fc(x)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/apollon-22/anaconda3/envs/dagr/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 103, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: CUDA error: CUBLAS_STATUS_NOT_SUPPORTED when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`
AssertionError when running run_test.py with DSEC-Detection dataset
When attempting to run the run_test.py script, an AssertionError is encountered. I followed the guidelines provided in the DSEC-Detection to download, so I am uncertain why this error is occurring.
Command executed
CUDA_VISIBLE_DEVICES=$DEVICE python scripts/run_test.py --config config/dagr-s-dsec.yaml --use_image --img_net resnet50 --checkpoint data/dagr_s_50.pth --batch_size 4 --dataset_directory $DSEC_ROOT --output_directory $LOG_DIR
Error message
File "scripts/run_test.py", line 67, in <module>
metrics = run_test_with_visualization(test_loader, ema.ema, dataset=args.dataset)
File "/dagr/dagr/src/dagr/utils/testing.py", line 28, in run_test_with_visualization
for i, data in enumerate(tqdm.tqdm(loader, desc=f"Testing {name}")):
File "/miniconda3/envs/dagr/lib/python3.8/site-packages/tqdm/std.py", line 1181, in __iter__
for obj in iterable:
File "/miniconda3/envs/dagr/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 631, in __next__
data = self._next_data()
File "/miniconda3/envs/dagr/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 675, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/miniconda3/envs/dagr/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 51, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/miniconda3/envs/dagr/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 51, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/dagr/dagr/src/dagr/data/dsec_data.py", line 144, in __getitem__
detections_1 = self.dataset.get_tracks(image_index_1, mask=track_masks, directory_name=dataset.root.name)
File "/dagr/dagr/libs/dsec-det/src/dsec_det/dataset.py", line 110, in get_tracks
i_0, i_1 = self.get_index_window(index, len(img_idx_to_track_idx), sync=self.sync)
File "/dagr/dagr/libs/dsec-det/src/dsec_det/dataset.py", line 101, in get_index_window
assert 0 <= index < num_idx - 1
AssertionError
Aborted， why?
/dagr# CUDA_VISIBLE_DEVICES=$DEVICE python scripts/run_test_interframe.py --config config/dagr-s-dsec.yaml
--use_image
--img_net resnet50
--checkpoint data/dagr_s_50.pth
--batch_size 8
--dataset_directory data/DSEC_fragment
--no_eval
--output_directory $LOG_DIR
Aborted
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.