Models
YOLOX vs. MobileNet V2 Classification

YOLOX vs. MobileNet V2 Classification

Both YOLOX and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOX and MobileNet V2 Classification.

Models

icon-model

YOLOX

YOLOX is a high-performance object detection model.
icon-model

MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.
Model Type
Object Detection
--
Classification
--
Model Features
Item 1 Info
Item 2 Info
Architecture
CNN, YOLO
--
--
Frameworks
PyTorch
--
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
8.9k+
--
--
License
Apache-2.0
--
--
Training Notebook

Compare YOLOX and MobileNet V2 Classification with Autodistill

Compare YOLOX vs. MobileNet V2 Classification

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.