MobileNet_V2

ConvNet Image Classification

class lucid.models.MobileNet_V2(num_classes: int = 1000)

Overview

The MobileNetV2 class implements the MobileNet-v2 architecture, an advancement over MobileNet-v1. It introduces the concept of inverted residual blocks and linear bottlenecks, which significantly enhance efficiency and accuracy for mobile and embedded vision applications. This architecture is particularly optimized for lightweight and low-power tasks, making it suitable for real-time applications on mobile devices.

MobileNet-v2 architecture

Class Signature

class MobileNet_V2(nn.Module):
    def __init__(self, num_classes: int = 1000) -> None

Parameters

  • num_classes (int, optional): Number of output classes for the classification task. Default is 1000, commonly used for ImageNet.