Skip to content

Latest commit

 

History

History
64 lines (52 loc) · 4.61 KB

README.md

File metadata and controls

64 lines (52 loc) · 4.61 KB
Raw

Classification and Segmentation 4 Vietnamese Foods

Summary

  • In this project, I use Pytorch to perform classification and segmentation of 4 popular dishes in Vietnam.Also, to make image segmentation easy, I used additional library Segmentation Pytorch

Dataset 🥚

  • The data is taken from the dataset 30VNFoods, this dataset includes 30 dishes and I took 4 dishes: Bánh mì, Phở, Bánh tráng nướng và Cơm tấm

    Example

Models

  • I use a variety of models ranging from MLP to Simple CNN, miniVGG. Pre-trained models such as VGG16, ResNet18

  • For the Segmentation problem, I use the Unet structure with the encoders being pre-trained models to get the best results.

  • I use Wandb to track and compare experiments: Classification, Segmentation

How to run this project ❓

git clone https://github.com/Harly-1506/4VNfoods-Deep-learning.git

cd 4VNfoods_Deep_learning
#run classification
run classifi_main.py
#run segmentation
run seg_main.py

Note: When you run seg_main.py, it takes 8 to 10 minutes to prepare the data

Classification Results

Methods Accuracy Loss Val_Accuracy Val_Loss Test_accuracy
Resnet18_pretrained 99.926 6.78E-05 96.907 0.1106 95.886
Resnet18 99.486 0.0003 80.154 0.7141 78.663
VGG16_pretrained 99.266 0.0005 94.587 0.4035 95.758
VGG16 95.229 0.0030 78.350 0.6939 77.763
miniVGG 99.926 0.0001 82.989 0.6325 87.917
SimpleCNN 99.559 0.0008 86.597 0.3855 86.632
MLP_4hidden512node 53.651 0.0678 45.103 2.8904 47.043
MLP_3hidden1024node 44.403 0.1080 34.278 4.8297 38.946
MLP_3hidden512node 55.486 0.0707 40.721 5.5563 44.987
MLP_4hidden 47.706 0.0583 37.886 2.3706 38.303
MLP_3hidden 49.761 0.0512 36.082 3.0187 41.902
MLP_2hidden 48.844 0.0438 40.979 1.6916 41.516

Segmentation Results

Methods iou/valid iou banhmi iou banhtrang iou comtam iou pho iou_clutter
Unet_ResNet34 0.8625 0.8273 0.8529 0.7083 0.7099 0.9084
Unet-ResNet18 0.8828 0.8655 0.8897 0.7893 0.7571 0.9214
Unet-VGG16 0.8716 0.8627 0.8713 0.7395 0.7463 0.9146

Plot Val Accuracy

  • Classification: Example
  • Segmentation: image

Demo:

  • Demo program you can follow in this repository: Demo

Author: Harly

If you have any problems, please leave a message in Issues

Give me a star ⭐ if you find it useful, thanks