What are the categories in ImageNet?

What are the categories in ImageNet?

ImageNet has been mostly used for researching object recognition algorithms on the subset of 1000 categories selected for the ImageNet Challenge, with only 3 people categories ( scuba diver , bridegroom , and baseball player ).

What is the resolution of ImageNet?

The average resolution of an ImageNet image is 469×387. They are usually cropped to 256×256 or 224×224 in your image preprocessing step.

How long it takes to train ImageNet?

Finishing 90-epoch ImageNet-1k training with ResNet-50 on a NVIDIA M40 GPU takes 14 days. This training requires 10^18 single precision operations in total.

How to setup training data in ImageNet?

The training data is a subset of ImageNet containing the 1000 categories and 1.2 million images Image classification. data setup: create a folder or symlink with the name ilsvrc2012/ where you have stored and unpacked the data files and, when loading the dataset, use the data_dir input argument to specify the data’s folder path.

What are the parts of the ImageNet dataset?

The ImageNet dataset consists of three parts, training data, validation data, and image labels. The training data contains 1000 categories and 1.2 million images, packaged for easy downloading. The validation and test data are not contained in the ImageNet training data (duplicates have been removed).

How to create image classification in ilsvrc2012?

Image classification. data setup: create a folder or symlink with the name ilsvrc2012/ where you have stored and unpacked the data files and, when loading the dataset, use the data_dir input argument to specify the data’s folder path. description: Contains image filenames and label annotations for image classification.

Is the validation and test data in the ImageNet?

The validation and test data are not contained in the ImageNet training data (duplicates have been removed). The validation and test data consists of 150,000 photographs, collected from flickr and other search engines, hand labeled with the presence or absence of 1000 object categories.