October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Using the pre-existing COCO dataset
For this implementation, we will be using the COCO dataset. This is a great resource dataset for training YOLOv2 to detect, segment, and caption images on a large scale. Download the dataset from http://cocodataset.org and run the following command in the terminal:
- Get the training dataset:
wget http://images.cocodataset.org/zips/train2014.zip
- Get the validation dataset:
wget http://images.cocodataset.org/zips/val2014.zip
- Get the train and validation annotations:
wget http://images.cocodataset.org/annotations/annotations_trainval2014.zip
Now, let's convert the annotations in the COCO format to VOC format:
- Install Baker:
pip install baker
- Create the folders to store the images and annotations:
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