model_inception_v3

Architecture from <a href="https://arxiv.org/abs/1512.00567">Rethinking the Inception Architecture for Computer Vision</a>
The required minimum input size of the model is 75x75.

Provides access to datasets, models and preprocessing
facilities for deep learning with images. Integrates seamlessly
with the 'torch' package and it's 'API' borrows heavily from
'PyTorch' vision package.

Daniel Falbel

torchvision

Models, Datasets and Transformations for Images

Christophe Regouby

Akanksha Koshti

Derrick Richard

 RStudio

model_inception_v3 function

<dl><dt>pretrained</dt>
<dd>(bool): If <code>TRUE</code>, returns a model pre-trained on ImageNet</dd>
<dt>progress</dt>
<dd>(bool): If <code>TRUE</code>, displays a progress bar of the download to stderr</dd>
<dt>...</dt>
<dd>Used to pass keyword arguments to the Inception module:<ul>
<li>aux_logits (bool): If <code>TRUE</code>, add an auxiliary branch that can improve training.
Default: TRUE</li>
<li>transform_input (bool): If <code>TRUE</code>, preprocess the input according to the method with which it
was trained on ImageNet. Default: FALSE</li>
</ul></dd></dl>

Arguments

Architecture from <a href='https://arxiv.org/abs/1512.00567'>Rethinking the Inception Architecture for Computer Vision</a>
The required minimum input size of the model is 75x75.

Inception v3 model — model_inception_v3

<dl>

<dt>pretrained</dt>
<dd>(bool): If <code>TRUE</code>, returns a model pre-trained on ImageNet</dd>


<dt>progress</dt>
<dd>(bool): If <code>TRUE</code>, displays a progress bar of the download to stderr</dd>


<dt>...</dt>
<dd>Used to pass keyword arguments to the Inception module:<ul>
<li>aux_logits (bool): If <code>TRUE</code>, add an auxiliary branch that can improve training.
Default: TRUE</li>
<li>transform_input (bool): If <code>TRUE</code>, preprocess the input according to the method with which it
was trained on ImageNet. Default: FALSE</li>
</ul></dd>

</dl>

model_inception_v3: Inception v3 model

Description

Usage

Arguments

See Also