![]() ![]() So you might want to slice the images list to the first n. Note that this will save all images from the specified category. With open('.path_saved_ims/coco_person/' + im, 'wb') as handler: We can now use requests to GET the images and write them into a local folder: # Save the images into a local folder Which returns a list of dictionaries with basic information on the images and its url. # Get the corresponding image ids and images using loadImgs # Specify a list of category names of interestĬatIds = coco.getCatIds(catNms=) # instantiate COCO specifying the annotations json pathĬoco = COCO('.path_to_annotations/instances_train2014.json') Now here's an example on how we could download a subset of the images containing a person and saving it in a local file: from co import COCO Download one of the annotations jsons from the COCO dataset.Here's a demo notebook going through this and other usages. To download images from a specific category, you can use the COCO API.
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