Comments (2)
For a single image it will be: outputs[0,y,x,0]
from densedepth.
outputs = predict(model, inputs)
outputs[0,:,:,0]
right? :)
from densedepth.
Related Issues (20)
- Quantization
- DenseNet (Pretrained=Flase) in the Pytorch version
- why it works better on hface than locally with same model acquired from hface ?
- mesh export ? IS it somehow possible ?
- Error in DenseNet Model pytorch, upsample class
- Poor predictions from pre-trained model? HOT 1
- how can i get real depth of objects? whether object is near/close, moderate distance or far away?
- how to run this on our own dataset HOT 3
- Error when Running on Higher-Resolution Images
- AttributeError: 'Conv2D' object has no attribute 'outbound_nodes' HOT 2
- TensorFlow and Matlab
- Uncertainty estimation
- Units of the depth estimation
- Problem while running evaluate.py
- goood job
- TypeError:montage() got an unexpected keyword argument 'multichannel' HOT 2
- Questions about the loss function of the Pytorch
- Problem with testing on my data
- Link to pretrained models not working HOT 2
- Question about Validation Data
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 densedepth.