We wanted to convert our phones into a pokedex for animals. Point and recognize the creature in front of you with its species.
Our childhood and of course Pokemon
As of now, we were able to run an object detector which given an image recognizes the object present in it. It outputs a probability score from a list of classes that could be assigned to an image.
We used AWS Sagemaker to train an image classifier. The platform had a built in image classification algorithm which we used to train on the caltech 256 dataset. We came across the iWildcam 2019 dataset to train an animal classifier but couldn't get to training one on it in the timeframe. Our learning curve to use AWS Sagemaker was steep and we encountered numerous issues to get the training done.
Lack of GPU instances to train faster. First exposure to AWS Sagemaker made it difficult for us to figure out the concepts of buckets, notebook instances and compute instances.
Finally being able to train a model on the cpu that does reasonably well to identify objects
Technical skills - AWS, Pytorch, Hyperparameter tuning
Life skills - Patience, How to handle Disappointment
Train an animal classifier
Python, Caltech dataset, AWS sagemaker resources