Upload 2 files

.gitattributes

@@ -73,3 +73,4 @@ imgs-6bcad3d.tar filter=lfs diff=lfs merge=lfs -text
 upscaled.tar filter=lfs diff=lfs merge=lfs -text
 fin-twref-images-7bca4c.tar filter=lfs diff=lfs merge=lfs -text
 s5cmd filter=lfs diff=lfs merge=lfs -text
+ocr_vqa_200k_dataset.json filter=lfs diff=lfs merge=lfs -text

ocr_vqa_200k_dataset.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9d2bb4c67462e2649be5099a3b790c95ad073fe46243310b79a1d4c8bee75ed
+size 112962519

ocr_vqa_200k_loadDataset.py

@@ -0,0 +1,100 @@
+import json
+import sys
+import os
+import urllib.request as ureq
+import pdb
+
+download=1 # 0 if images are already downloaded
+
+###############################################################
+######################### load dataset json file ###############
+################################################################
+with open('dataset.json', 'r') as fp:
+        data = json.load(fp)
+
+## dictionary data contains image URL, questions and answers ##
+
+
+
+
+################################################################
+############### Script for downloading images ##################
+################################################################
+## Make a directory images to store all images there ##########
+if download == 1:
+    os.mkdir('./images')
+    for k in data.keys():
+        ext=os.path.splitext(data[k]['imageURL'])[1]
+        outputFile='images/%s%s'%(k,ext)
+        pdb.set_trace()
+        ureq.urlretrieve(data[k]['imageURL'],outputFile)    
+
+
+
+#################################################################
+################### Example of data access #####################
+################################################################
+for k in data.keys():
+    ext=os.path.splitext(data[k]['imageURL'])[1]
+    imageFile='images/%s%s'%(k,ext)
+
+    print('************************')
+    print('Image file: %s'%(imageFile))
+    print('List of questions:')
+    print(data[k]['questions'])
+    print('List of corresponding answers:')
+    print(data[k]['answers'])
+    print('Use this image as training (1), validation (2) or testing (3): %s'%(data[k]['split']))
+    print('*************************')
+
+
+
+
+
+######################################################################
+########################### Get dataset stats ########################
+######################################################################
+genSet=set()
+for k in data.keys():
+    genSet.add(data[k]['genre'])
+
+
+
+numImages=len(data.keys())
+numQApairs=0
+numWordsInQuestions=0
+numWordsInAnswers=0
+numQuestionsPerImage=0
+ANS=set() # Set of unique answers
+authorSet=set()
+bookSet=set()
+
+
+for imgId in data.keys():
+    numQApairs = numQApairs+len(data[imgId]['questions'])
+    numQuestionsPerImage = numQuestionsPerImage + len(data[imgId]['questions'])
+    authorSet.add(data[imgId]['authorName'])
+    bookSet.add(data[imgId]['title'])
+
+    for qno in range(len(data[imgId]['questions'])):
+        ques=data[imgId]['questions'][qno]
+        numWordsInQuestions = numWordsInQuestions+len(ques.split())
+    for ano in range(len(data[imgId]['answers'])):
+        ans=data[imgId]['answers'][ano]
+        ANS.add(ans)
+        numWordsInAnswers = numWordsInAnswers+len(str(ans).split())
+
+
+
+print("--------------------------------")
+print("Number of Images: %d" %(numImages))
+print("Number of QA pairs: %d" %(numQApairs))
+print("Number of unique author: %d" %(len(authorSet)))
+print("Number of unique title: %d" %(len(bookSet)))
+print("Number of unique answers: %d" %(len(ANS)))
+print("Number of unique genre: %d" %(len(genSet)))
+print("Average question length (in words): %.2f" %(float(numWordsInQuestions)/float(numQApairs)))
+print("Average answer length (in words): %.2f" %(float(numWordsInAnswers)/float(numQApairs)))
+print("Average number of questions per image: %.2f" %(float(numQuestionsPerImage)/float(numImages)))
+print("--------------------------------")
+