HotDog-Nothotdog

"What would you say if I told you there is a app on the market that tell you if you have a hotdog or not a hotdog.

Collect the data

Training Data

1- HotDogs images

2- NotHotdogs Images(Random images)

We can use some food image datasets Like

  http://mmspg.epfl.ch/food-image-datasets
  
  https://www.vision.ee.ethz.ch/datasets_extra/food-101/
  
  or use imagenet

How to train it?

Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars.

![Alt text](/CNN.jpg?raw=true "Optional Title")

Model, That I've used!!

You can use this model too

Layer	Description
Input	128x128x1 Gray scale image
Convolution 8x8	4x4 subsampling
ELU
Convolution 5x5	2x2 subsampling
ELU
Convolution 5x5	2x2 subsampling
Flatten
Dropout	.2 dropout probability
ELU
Fully connected	output 512
Dropout	.5 dropout probability
ELU
Fully connected	output 2
Softmax	output 2

(use this pre-trained model -- model.h5)-- thanks to Kevin