deep-head-pose
:fire::fire: Deep Learning Head Pose Estimation using PyTorch. (by natanielruiz)
tf-keras-deep-head-pose
A tensorflow & keras implementation of Deep Head Pose (by Oreobird)
deep-head-pose | tf-keras-deep-head-pose | |
---|---|---|
2 | 1 | |
1,530 | 70 | |
- | - | |
0.0 | 0.0 | |
12 months ago | almost 2 years ago | |
Python | Python | |
GNU General Public License v3.0 or later | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deep-head-pose
Posts with mentions or reviews of deep-head-pose.
We have used some of these posts to build our list of alternatives
and similar projects.
- [D] SOTA Head Pose Estimation Models
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What does model.eval() do in pytorch?
I am using this code, and saw model.eval() in some cases.
tf-keras-deep-head-pose
Posts with mentions or reviews of tf-keras-deep-head-pose.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Attempting to train a muli loss model in Keras. Failing miserably!
All I am doing is downloading the code which is available on github (https://github.com/Oreobird/tf-keras-deep-head-pose) so that I can train it myself. However, I am ashamed to say that even just attempting this is giving me issues with regards to the models losses not converging. Where the losses reported in the HopeNet paper gets down to less than 5 per angle, my losses are in the hundreds.
What are some alternatives?
When comparing deep-head-pose and tf-keras-deep-head-pose you can also consider the following projects:
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)