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KarpathySplit.py

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+# coding: utf-8
+
+# # Karpathy Split for MS-COCO Dataset
+import json
+from random import shuffle, seed
+
+seed( 123 )
+
+num_val = 5000
+num_test = 5000
+
+val = json.load( open('./data/annotations/captions_val2014.json', 'r') )
+train = json.load( open('./data/annotations/captions_train2014.json', 'r') )
+
+# Merge together
+imgs = val['images'] + train['images']
+annots = val['annotations'] + train['annotations']
+
+shuffle( imgs )
+
+# Split into val, test, train
+dataset = {}
+dataset[ 'val' ] = imgs[ :num_val ]
+dataset[ 'test' ] = imgs[ num_val: num_val + num_test ]
+dataset[ 'train' ] = imgs[ num_val + num_test: ]
+
+# Group by image ids
+itoa = {}
+for a in annots:
+    imgid = a['image_id']
+    if not imgid in itoa: itoa[imgid] = []
+    itoa[imgid].append(a)
+
+
+json_data = {}
+info = train['info']
+licenses = train['licenses']
+
+split = [ 'test', 'val', 'train' ]
+
+for subset in split:
+
+    json_data[ subset ] = { 'type':'caption', 'info':info, 'licenses': licenses,
+                           'images':[], 'annotations':[] }
+
+    for img in dataset[ subset ]:
+
+        img_id = img['id']
+        anns = itoa[ img_id ]
+
+        json_data[ subset ]['images'].append( img )
+        json_data[ subset ]['annotations'].extend( anns )
+
+    json.dump( json_data[ subset ], open( './data/annotations/karpathy_split_' + subset + '.json', 'w' ) )