This project classifies given images as dog image or not.
- Python 3
- Anaconda
git clone https://github.com/rajashekar/dog_classifier.git
cd dog_classifier
Create the environment
conda env create -f environment.yml
Once dog_classifier environment is created. Activate the environment
conda activate dog_classifier
Run the check images to classify images
python check_images.py
Sample output
CNN Model : vgg
Number of Images : 40
Number of Dog images : 30
Number of Not-a Dog images : 10
100.00% Correct Dogs
93.33% Correct Breed
100.00% Correct Not-a Dog
87.50% Match
** Total Elapsed Runtime: 0:0:19
By default vgg is used, to use different arch like resnet you can do like below
python check_images.py --dir pet_images/ --arch resnet --dogfile dognames.txt
To check the classification based on alexnet
python check_images.py --dir pet_images/ --arch alexnet --dogfile dognames.txt
To run as batch to compare results of vgg, resnet and alexnet
sh run_models_batch.sh