Emotion Detector CNN
Spot emotions like a pro with next-level CNNs and TIMM model magic.
Project Description
This project uses Convolutional Neural Networks (CNNs) with pretrained TIMM models to classify emotions like a boss.
Boosted by dope augmentation tricks like random resizing, flipping, color jitter, CutMix, and MixUp for top-tier generalization.
Smart dataset splits for training and validation ensure the model’s performance is on point.
Key Features
TIMM Model Swagger
High-performance pretrained models for reliable emotion detection.
Augmentation All-Stars
CutMix, MixUp, and more spice up data for better results.
Training Smarts
Optimized splits for max accuracy and generalization.
Technical Details
Python
Versatile programming language for web development, data science, and automation
PyTorch
Deep learning framework with dynamic computation graphs
CNN
Convolutional Neural Networks for image processing and recognition
timm
PyTorch image models library with pre-trained models