anilbatra2185/road_connectivity

Improved Road Connectivity by Joint Learning of Orientation and Segmentation (CVPR2019)

road_connectivity's Issues

Question about SapceNet dataset processing

Hi,
I tried your Data Preparation process to the step of Split Datasets. I did got the full folder with 2780 images. However, using your code, it came out 1999 images in train folder and 566 images in val folder. The result is different from '2213 images for training and 567 for testing' in your CVPR2019 essay.
Should the 566 images be used for testing? Should I pull some images out from train folder to make a val dataset?
I really want to use the same dataset with you to evaluate the performance of our network.
Thanks a lot!

RuntimeError: Given groups=1, weight of size [64, 3, 7, 7], expected input[16, 256, 256, 3] to have 3 channels, but got 256 channels instead

python train_mtl.py

No create_crops.py

Hi,

there is no create_crops.py in your file,please help!

Thanks!

prepare_spacenet.sh: No such file or directory

share .pth.tar file

Thank you very much for your work! I trained the deepglobe dataset with your train_mtl.py , but the prediction is not very good, even worse than using segmentation network like unet or linknet. Could you share your model file? And other question,How the orientation task enhance the final result,add two tasks result?Thanks a lot!

AWS account expired.how to download spacenet data?

Is there any other way to download the spacenet 3 data?

name error: name 'utils' is not defined

when i ran trian_mtl.py

AttributeError: 'MultiGraph' object has no attribute 'node'

Good evening,

when I am trying to start training the network, I get the following error:

File "C:\Users...\road_connectivity-master\data_utils\graph_utils.py", line 53,
in simplify_graph
full_segments = np.row_stack([graph.node[s]["o"], ps, graph.node[e]["o"]])
AttributeError: 'MultiGraph' object has no attribute 'node'

Experimental hardware device and the pre-training model

What is the GPU version used in the model training experiments in your article? What is the number of GPUs? How long does it take to train a model? And will you release the pre-training model?

how to infer on the test set

Thanks for your great work! I've trained the model successfully, and I want to use the model to infer on the test set and submit the predicted pictures on deepglobe website to evaluate. However, I doesn't find the infer code in it. Can you give me some advices?

Details of junction learning

Thank you very much for your work, it helped me a lot. I want to know more about junction learning, where do I need to find its details or implementation? Thanks again

precision, recall and f1 metrics

Hi, Anil Batra. I read your paper, I think it helps me.However, I have a question. IOU can reach your level, but precision, recall and f1 are a lot worse in DeepGlobe . Whether precision, recall and f1 metrics are relaxed in your paper. Can you tell me how to calculate these metrics in you paper. Looking forward to your answer,thank you!

Could you share the code to convert DeepGlobe mask label to .csv file？

Thank you for your great work! I have already read #13 , but I cannot convert DeepGlobe to .csv for APLS. Could you share your solution? It will be of great help.

Training file for Road connectivity refinement

Thank you for your wonderful work! Looking forward to your source code for road connectivity refinement. I think I will get many inspirations from that.

How to evaluate DeepGlobe graph with APLS metric?

Hi, thank you for your response.
I wonder how to evaluate the inferred graph using APLS metric?
What data structure do you use to evaluate, and what's the key attribution that the data structure must have?
The reason why I ask so is that, according to https://github.com/CosmiQ/apls, the evaluation metric seems to be connected with lon/lat coordinate or utm coordinate.
Source codes may help more! Thx!

how can we produce training dataset with DeepGlobe?

In the paper, I see you use linestring(this information is in the dataset SpaceNet ). However, There is no linestring datastruct in dataset Deepglobe(there are just two kinds of pictures binary gt pics and satelite pics). So how can we produce training dataset with DeepGlobe? Thank you very much!

add: Assertion `pos >= 0 && pos < buffer.size()` failed

Thanks for your fantastic work!When I tried to train this model,I meet this problem:
Traceback (most recent call last):
File "train_mtl.py", line 427, in
train(epoch)
File "train_mtl.py", line 264, in train
torch.autograd.backward([loss1, loss2])
File "/home/sy/anaconda3/envs/connect/lib/python2.7/site-packages/torch/autograd/init.py", line 99, in backward
variables, grad_variables, retain_graph)
RuntimeError: torch/csrc/autograd/input_buffer.cpp:14: add: Assertion pos >= 0 && pos < buffer.size() failed.
Hope you can give me some instruction to solve this problem.

training miou 47~48

Is it corre that the first 30 epochs keep miou 47~48？

Some questions about the evalution metrics

Hi,
I notice that you used a buffer of 4 pixels in your evaluations in your paper. And I noticed that there is function called "relaxed_f1". However, I find you do not use the "relaxed_f1" function in your main training or test stage (i.e., train_mtl.py).

So my question is that the results reported in your paper used "the bufffer evalution" or not? It confused me.

Producing DeepGlobe training dataset

Thank you for your great job!!! I have seen the colsed issue which askes for the training DeeoGlobe dataset, but I can't find the code for computing the road line string ground-truths. Where can I find the code?

feature request: ALPS compute function

Hi,

Could you please share your APLS function to evaluate on DeepGlobe dataset?

Best regards.

utils.loss

can't find loss in the utils;
lead to ModuleNotFoundError: No module named 'utils.loss'

split_data.sh: line 43: /data/deepglobe/train.txt: No such file or directory split_data.sh: line 51: /data/deepglobe/val.txt: No such file or directory

I have put the deepglobe data in the right path:

--data/deepglobe/train val.txt train.txt
--data/deepglobe/train/_sat.jpg _mask.png

but when I run:

bash split_data.sh /deepglobe/train /data/deepglobe _sat.jpg _mask.png

it still told me:
split_data.sh: line 43: /data/deepglobe/train.txt: No such file or directory
split_data.sh: line 51: /data/deepglobe/val.txt: No such file or directory

This question has been solved when I use a deep path ! thank you ! you can delete this question~ because it is not a common problem

erased_label in evaluation

Hello,
I had a look at the evaluation function for the train_refine_pre.py script at line 260:

road_connectivity/train_refine_pre.py

Line 269 in 4559e3b

inputs, labels, erased_label = data

could you please explain what the variable erased_label contains?

Thanks

NumbaWarnings and RuntimeWarnings / console log attaced

Hi,

I get many NumbaWarnings and Runtime Erros, mainly for code written within the sknw.py, and then training fails. I hope you can find why this is happening by reading the attached log message that I get in my cmd.

cmd_log.txt

runtimeerror: input and target batch or spatial sizes don't match:target [16 * 256 * 3],input [16*37*256*256]

CUDA_VISIBLE_DEVICES=0,1 python train_mtl.py --config config.json --dataset deepglobe --model_name "LinkNet34MTL" --exp dg_stak_mtl

how to get

train_crops.txt # created by script
I do not know by which script

Spacenet Road Extraction Dataset

ImportError: No module named rotate_utils

If you don't mind, may I ask the question: have you update all the code or do I do something wrong? I try:python road_dataset.py

why you return -torch.mean(loss)?

understand! sorry!

Actual model code

Hi,

I was wondering when the actual model code becomes available?

Thanks!

train_crops.txt

direction of the direction vector

It's a great job, but I have some questions about some details in the code.

1. In the getKeypoints function (in affinity_utils.py), when the points list is updated, the keypoint list_is also updated, which results in the final keypoint list recorded repeatedly the same road line. What is the purpose of doing this? Is it because the later getVectorMapsAngles function will iterate through each repeatedly recorded road line, the later records of the same road line will overwrite the previous results, so there is no impact on generating angle?

2. For the keypoint generated by a road line, are the points close to the (0,0) point at the top of the list?
   

3. The directional vectors generated in the code are based on the pixel coordinate system. If 2 is right, I think that the direction of vectors point from right to left and bottom to top in a image.

4. In the visualize_task.ipybn, you use the plotVecMap function to visualize the arrow. To the best of my knowledge, the plt.quiver() function you used plot the arrow in cartesian coordinate system rather than the pixel coordinate system. For the direction, the x-positive direction is the same for both, while the y-axis has the opposite positive direction, so I think it should be V*-1 instead of U*-1 in plotVecMap function.

Post-training

Thank you for your great work. Is the post-training file released yet? Or please tell me the input of fine-tuning is the output of the test set in the mul network？thanks

Cannot train the module

I run the following command in my terminal and I get the following message:

$ set CUDA_VISIBLE_DEVICES=0 & python train_mtl.py --config config.json --dataset deepglobe --model_name "LinkNet34MTL" --exp dg_L34_mtl --multi_scale_pred false
Random Seed:  7
Single Cuda Node is avaiable
Training with dataset => DeepGlobeDataset
****************************************************************************************************
Trainable parameters for Model LinkNet34MTL : 22.004903 M
****************************************************************************************************
...
...
Some numba warnings and runtime warnings
...
...


[>....... 1/1 ............]S:9s492ms|T:0ms|Loss: -0.284238 | VecLoss: 4.207048 | road miou: 28.0047%(18.9634%) | angle miou: 0.2155%

Traceback (most recent call last):
  File "train_mtl.py", line 443, in <module>
    main()
  File "train_mtl.py", line 434, in main
    train(epoch)
  File "train_mtl.py", line 294, in train
    write=True,
  File "C:\Users\...\road_connectivity-master\utils\util.py", line 147, in performMetrics
    100 * fwavacc,
TypeError: a bytes-like object is required, not 'str'

Do you know how to solve this issue?

requirements.txt

Hi,

Thanks for making the code available. For some reason I am unable to run this code on my system due to some unmet dependencies. Could you please share a detailed requirements.txt file.

What type of the iou in the code is?

Hi, There are two type of Road IOU in your paper IoU^r and IoU^a. What type of the iou in the code is?