<p>Universal feature extraction, new models, new weights, new test sets.</p>
<p>Universal feature extraction, new models, new weights, new test sets.</p>
<ul>
<ul>
<li>All models support the <code>features_only=True</code> argument for <code>create_model</code> call to return a network that extracts features from the deepest layer at each stride.</li>
<li>All models support the <code>features_only=True</code> argument for <code>create_model</code> call to return a network that extracts features from the deepest layer at each stride.</li>
@ -467,6 +467,8 @@
</ul>
</ul>
</li>
</li>
<li>Add 'real' labels for ImageNet and ImageNet-Renditions test set, see <ahref="results/README.md"><code>results/README.md</code></a></li>
<li>Add 'real' labels for ImageNet and ImageNet-Renditions test set, see <ahref="results/README.md"><code>results/README.md</code></a></li>
<li>Train script and loader/transform tweaks to punch through more aug arguments</li>
<li>README and documentation overhaul. See initial (WIP) documentation at <ahref="https://rwightman.github.io/pytorch-image-models/">https://rwightman.github.io/pytorch-image-models/</a></li>