xiaoerlaigeid / bird_classification

Fine-grained classification of bird images from Caltech-UCSD Birds-200-2011 dataset

bird_classification

Fine-grained classification of bird images from Caltech-UCSD Birds-200-2011 dataset The required-dataset could be found at Caltech-UCSD Webpage for the same.

Place all the Downloaded Data in the "/data" folder and run "convert.py" (python convert.py). This will convert the data in the required format i.e. the train and test file data (labels, image-locations and bounding boxes) will be placed in separate files.

Now a sample command to run the (main)code:

python main.py --batch_size 8 --val_ratio 0.1 --num_epochs 5000 --gpu_mem_frac 0.5 --model vgg

This will create a csv file which will store the prediction for each test-image indexed by its id.

TODO

1. Use Predictions and Test_labels to show accuray on test-data
2. Add Visualization for some random test/train images
3. Check the code end-to-end
4. Add other Deep-Neural Net Models