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### Trained on [ COCO] ( https://cocodataset.org/#home ) (50 GB, 2017 challenge)
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``` bash
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- %%bash
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-
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- mkdir coco
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- cd coco
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- mkdir images
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- cd images
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-
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- wget -c http://images.cocodataset.org/zips/train2017.zip
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- wget -c http://images.cocodataset.org/zips/val2017.zip
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- wget -c http://images.cocodataset.org/zips/test2017.zip
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- wget -c http://images.cocodataset.org/zips/unlabeled2017.zip
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-
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- unzip train2017.zip
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- unzip val2017.zip
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- unzip test2017.zip
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- unzip unlabeled2017.zip
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-
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- rm train2017.zip
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- rm val2017.zip
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- rm test2017.zip
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- rm unlabeled2017.zip
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-
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- cd ../
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- wget -c http://images.cocodataset.org/annotations/annotations_trainval2017.zip
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- wget -c http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip
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- wget -c http://images.cocodataset.org/annotations/image_info_test2017.zip
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- wget -c http://images.cocodataset.org/annotations/image_info_unlabeled2017.zip
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-
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- unzip annotations_trainval2017.zip
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- unzip stuff_annotations_trainval2017.zip
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- unzip image_info_test2017.zip
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- unzip image_info_unlabeled2017.zip
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-
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- rm annotations_trainval2017.zip
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- rm stuff_annotations_trainval2017.zip
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- rm image_info_test2017.zip
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- rm image_info_unlabeled2017.zip
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+ git clone https://github.com/AndreiMoraru123/ContextCollector.git
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+ cd ContextCollector
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+ make
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```
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#### Via the [ Python API] ( https://github.com/cocodataset/cocoapi )
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