avirambh / scopeflow Goto Github PK
View Code? Open in Web Editor NEWDynamic Scene Scoping for Optical Flow (CVPR 2020)
License: Apache License 2.0
scopeflow's People
Contributors
Stargazers
Watchers
scopeflow's Issues
checkpoints/KITTI_comb/checkpoint_best.ckpt always gives occlusion maps of all zeros
Dear Authors,
1). I got occlusion maps of all zeros when evaluating using the pretrained model "checkpoints/KITTI_comb/checkpoint_best.ckpt".
2). However, when I overwrite "checkpoints/KITTI_comb/checkpoint_best.ckpt" with the files moving from "checkpoints/Sintel_comb/checkpoint_best.ckpt", and did the same thing in 1), the occlusion map is not zero.
Was the occlusion being trained when creating the checkpoint "checkpoints/KITTI_comb/checkpoint_best.ckpt"?
Thank you very much!
=====
PS.
My environment is
python 3.7.3
pytorch 1.1.0
CUDA 9.0
The correlation package has been installed based on the instruction in the IRR-PWC repository.
Question about the code
Hi!
Thanks for sharing such an excellent work.
I have read the paper and code of ScopeFlow, And I found something confusing problems blow:
1.augmentation.py is used to perform geometry augmentation, and you have set min_rotate and max_rotate to -0.2 and 0.2. But the rotate coefficient will be generate randomly between [0.2, 0.2] such as line 261 or line 791, you set rotate coefficient to [-0.2, 0.2], but when generate random coefficent you use [-min_rotate, max_rotate], and thus rotate coefficient is generated between [0.2,0.2], which means always 0.2.
phi.uniform_(-min_rotate, max_rotate)
min_rotate=-1 * self._args.aug_rotate, max_rotate=self._args.aug_rotate,
aug_rotate: 0.2
2.According to the find_invalid() in file augmentation, when random generated zoom < 1.0, the affine matrix will never be valid, as if zoom<1.0, the corners of transformed img will be out of the border of source img.
Expecting for your replies! Thanks again!
Error during eval on sintal.
Validate: 0% 0/23 [00:00<?, ?it/s]error in correlation_forward_cuda_kernel: invalid device function
Traceback (most recent call last):
File "evaluate.py", line 41, in <module>
evaluate()
File "evaluate.py", line 37, in evaluate
validation.validate(args)
File "/content/ScopeFlow/lib/validation.py", line 93, in validate
res = train_and_val(args)
File "/content/ScopeFlow/lib/pipeline_wrapper.py", line 87, in train_and_val
validation_augmentation=validation_augmentation)
File "/content/ScopeFlow/lib/runtime.py", line 676, in exec_runtime
augmentation=validation_augmentation).run()
File "/content/ScopeFlow/lib/runtime.py", line 528, in run
loss_dict_per_step, output_dict, batch_size = self._step(example_dict)
File "/content/ScopeFlow/lib/runtime.py", line 451, in _step
loss_dict, output_dict = self._model_and_loss(example_dict)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/content/ScopeFlow/lib/configuration.py", line 85, in forward
output_dict = self._model(example_dict)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/content/ScopeFlow/models/IRR_PWC_V2.py", line 120, in forward
out_corr_relu_f = self._correlate(x1, x2_warp)
File "/content/ScopeFlow/models/IRR_PWC_V2.py", line 275, in _correlate
out_corr = self.correlation(x1, x2_warp)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__
result = self.forward(*input, **kwargs)
File "/content/ScopeFlow/models/correlation_package/correlation.py", line 59, in forward
result = CorrelationFunction(self.pad_size, self.kernel_size, self.max_displacement, self.stride1, self.stride2, self.corr_multiply)(input1, input2)
File "/content/ScopeFlow/models/correlation_package/correlation.py", line 27, in forward
self.pad_size, self.kernel_size, self.max_displacement,self.stride1, self.stride2, self.corr_multiply)
RuntimeError: CUDA call failed (correlation_forward_cuda at correlation_cuda.cc:79)
How do i fix this error?
How to inference on my own images?
Thank you for your great work! what are the necessary steps to test your given model on my own datasets?
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.