UniGaze Easy Loader
A tiny, dependency-light Python package to load UniGaze pretrained models from Hugging Face.
📦 Installation
Install a matching PyTorch first.
pip install torch==2.0.1 torchvision==0.15.2 --index-url https://download.pytorch.org/whl/cu118
pip install timm==0.3.2
pip install unigaze
🚀 Quick Start
import torch
model = unigaze.load("unigaze_h14_joint", device="cuda") # downloads weights from HF on first use
# Input: normalized batch (B, 3, 224, 224)
image_normalized_batch = torch.ones((10, 3, 224, 224), device="cuda")
# Output: {'pred_gaze': (B, 2)} with (pitch, yaw)
pred_gaze = model(image_normalized_batch)['pred_gaze']
print(pred_gaze.shape) # torch.Size([10, 2])
Release files for unigaze 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| unigaze-0.1.3.tar.gz | 16.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| unigaze-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.4 kB
Release files / unigaze-0.1.3.tar.gz
| Download URL | unigaze-0.1.3.tar.gz |
|---|---|
| Size | 16.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / unigaze-0.1.3-py3-none-any.whl
| Download URL | unigaze-0.1.3-py3-none-any.whl |
|---|---|
| Size | 16.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/6.2.0 CPython/3.9.25
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