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A simple python implemented frame-by-frame visual odometry with SuperPoint feature detector and SuperGlue feature matcher.

Python 100.00%

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python-vo's Issues

ground truth怎样获得

您好,运行程序后,有以下两个问题想请教您:
1. 最后生成的AvgError的图只有一个红点,并未有完整的轨迹,是什么问题?
2. 我是否可以用我自己的图片在此程序上进行图像匹配,请问groundtruth文件怎样能获得?

sift+superglue

您好,请问有尝试复现superglue文章里面的sift+superglue吗?最近一直在尝试,一直没有进展,希望可以交流

Error when run TUM dataset

I try to run code in TUM datasets but get the error message.

Traceback (most recent call last):
File "main.py", line 109, in
run(args)
File "main.py", line 65, in run
loader = create_dataloader(config["dataset"])
File "/home/zhy/PyProject/Python-VO/DataLoader/init.py", line 9, in create_dataloader
loader = eval(code_line)
File "", line 1, in
File "/home/zhy/PyProject/Python-VO/DataLoader/TUMRGBLoader.py", line 32, in init
self.read_imgs()
File "/home/zhy/PyProject/Python-VO/DataLoader/TUMRGBLoader.py", line 76, in read_imgs
rgb_list = lines[:, 1]
IndexError: too many indices for array

I use this code for running:
python main.py --config params/tumrgb_superpoint_supergluematch.yaml

The TUM dataset is organized as follows:
├ TUM
└rgbd_dataset_freiburg1_360
   └── depth
└ ...
   └── rgb
└ ...
   └── depth.txt
   └── rgb.txt
   └── rgbd_gt.txt

How to fix this error?

result_eval.py throwing an error

When I try running the result_eval.py, I get the following error:
result_eval.py:21: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
return np.array(img_ids), np.array(est_points), np.array(gt_points)
Traceback (most recent call last):
File "result_eval.py", line 70, in
main()
File "result_eval.py", line 38, in main
errors = np.linalg.norm((gt_xyz - est_xyz), axis=1)
ValueError: operands could not be broadcast together with shapes (8480,) (8480,3)

run error

Thank you for your good work. I encountered this problem when used
$ python main.py

Traceback (most recent call last):
File "main.py", line 124, in
run(args)
File "main.py", line 110, in run
cv2.imwrite("results/" + fname + '_new.png', img2)
UnboundLocalError: local variable 'img2' referenced before assignment

then,I put cv2.imwrite() into for()
it works ,but the four methods all just load the model,like this
INFO:root:{'descriptor_dim': 256, 'weights': 'outdoor', 'keypoint_encoder': [32, 64, 128, 256], 'GNN_layers': ['self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross', 'self', 'cross'], 'sinkhorn_iterations': 100, 'match_threshold': 0.2, 'cuda': 1, 'type': 'SuperGlue'}
INFO:root:creating SuperGlue matcher...
Loaded SuperGlue model ("outdoor" weights)

Thank you.

运行报错

您好,我在运行的时候,会报错UnboundLocalError: local variable 'img2' referenced before assignment,我在前面加了global img2 也没用,我的Python版本是3.7,请问您知道怎么解决吗?

convert matched keypoints to landmarks?

How do i convert the matched keypoints to 3d landmarks after apploying superglue matching ? Such that they can be converted into pointcloud and saved to database?

TUM RGBD Dataset fr3

请问有试过在TUM RGBD fr3 long office那个序列上跑吗?
我跑出来结果非常差,各种方法都得不到一个合理的轨迹,不知道是不是存在问题还是这个序列本身太难。

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