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The COCO dataset is very large for me to upload it to google colab. Is there any way I can directly download the dataset to google colab? asked Apr 7 '19 at 8:18 You can download it directly with wget! wget Also, you should use GPU instance which gives larger space at 350 GB. answered Apr 7 '19 at 10:34 korakot korakot 19. 5k 7 gold badges 71 silver badges 93 bronze badges You can download it to google drive and then mount the drive to Colab. from import drive ('/content/drive') then you can cd to the folder containing the dataset, for eg. import os ("drive/My Drive/cocodataset") answered Apr 9 '19 at 1:35 Ha Bom Ha Bom 2, 250 2 gold badges 12 silver badges 22 bronze badges One more approach could be uploading just the annotations file to Google Colab. There's no need to download the image dataset. We will make use of the PyCoco API. Next, when preparing an image, instead of accessing the image file from Drive / local folder, you can read the image file with the URL! # The normal method.
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Read from folder / Drive I = ('%s/images/%s/%s'%(dataDir, dataType, img['file_name'])) # Instead, use this! Url to load image I = (img['coco_url']) This method will save you plenty of space, download time and effort. However, you'll require a working internet connection during training to fetch the images (which of course you have, since you are using colab). If you are interested in working with the COCO dataset, you can have a look at my post on medium. answered May 6 at 7:28 Viraf Viraf 21 1 bronze badge Not the answer you're looking for? Browse other questions tagged python computer-vision google-colaboratory semantic-segmentation or ask your own question.