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Cleaning the Data

Preparing the Dataset

Creating the Model

The images that have been downloaded may not be of the same dimensions. It is preferred to have all the images in the dataset of uniform dimensionality. The fastai library has a function for this: 

Python3




bts = bts.new(
    item_tfms=RandomResizedCrop(224, min_scale=0.5),
    batch_tfms=aug_transforms())
dls = bts.dataloaders(path)
 






                        









													
													
												

												
												

													
													
All the images are resized to 224 x 224 which is a standard size for images in the training dataset. 

													
													
												

												
											

											
											

												
Identify Members of BTS — An Image Classifier

												
												

													
													
BTS is an eminent K-Pop band comprising of 7 members. This article looks at an image classifier that would recognize the name of the band member from a picture. The image classifier would be built using fastai. It is a deep learning library that aims to democratize deep learning. It is built on top of PyTorch, and has plethora of models with optimized weights that are ready-to-use. The application would be hosted on Binder, and the end product would look like this: 

													
													
												

												
												

													
													



													
													
												

												
											

										


										
										

											
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														Preparing the Dataset

													

														As is the case with any image classifier, the model needs to be trained on a dataset from which it can infer and extract the features corresponding to a particular category. The BTS Image Classifier would contain 7 categories (total number of members). The dataset can be prepared by manually collecting images of different members and then clubbing them in a folder of that category. In order to fasten this process, a Python script can be employed to create the dataset. The script would fetch images from Google Image Search. (Disclaimer: Using these images may lead to a copyright violation so proceed at your own risk)....
													

												
											

											
											

												
													

														Cleaning the Data

													

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														Creating the Model

													

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														Deploying the Model

													

														The images that have been downloaded may not be of the same dimensions. It is preferred to have all the images in the dataset of uniform dimensionality. The fastai library has a function for this:...
													

												
											

											
										


									

									

										
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												Preparing the Dataset
											
											
										

										

											
											
												Creating the Model