Comments (4)
Hi,
It means that the patch starts outside the original image which is assumed to be padded with zeros. So starting at a large negative offset for instance would guarantee a black output image. Similarly very large positive offsets also guarantee a black output image.
You can see the C++ code for extract_patches in ats/ops/extract_patches/extract_patches.cc. You can see in lines 108 and 109 that we check if a certain pixel is inside and then in line 119 we copy 0 if it is not inside.
Cheers,
Angelos
from attention-sampling.
Hm I am not sure I understand. What would the bounding box enforce? That the indices do not go out of the bbox? Then what does it mean to extract a patch centered at 0,0 with patch size 50,50? 0 to 50 or -25 to 25?
from attention-sampling.
Are these off-image indices bounded? Suppose I want to make a bounding box from each offset, a value may be outside the padded ones So the best thing to do would be clipping them to the range [0, MAXSIZE]
, right?
from attention-sampling.
The bounding box wouldn't enforce the offsets value range, I want them to be used on the original high dimensional images to perform cropping (for visualization purposes) and be able to compute some metrics (like IoU)
from attention-sampling.
Related Issues (20)
- RuntimeError: Couldn't compile and install ats.ops.extract_patches.libpatches HOT 4
- file not found HOT 2
- Allow use of a patch generator HOT 5
- Why using random sampling during inference and not pick instead the X patches with maximum attention? HOT 1
- C++ versions less than C++11 are not supported
- Suggestion of Environment (OS, package version, etc.) HOT 1
- Implementation of eq. 12 HOT 2
- Validation Accuracy Does not Change HOT 1
- MNIST noise overlaps signal
- expected_with_replacement
- Installation document no longer available
- Segmentation fault (core dumped) HOT 2
- What's the softmax temperature? HOT 1
- pip install runtime error: Couldn't compile and install ats.ops.extract_patches.libpatches HOT 4
- Unable to install on Macbook pro HOT 4
- It's not learning HOT 2
- Extracting weird patches HOT 6
- Batch size for all the experiments in the papaer HOT 2
- What is the role of "receptive field"? HOT 2
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.
from attention-sampling.