OCR/Results

How to process the 400k JSON files we've generated

Example

Image

Output

http://static.openfoodfacts.ovh/images/products/40193045/ingredients.12.full.json

{  
   u'responses':[  
      {  
         u'textAnnotations':[  
            {  
               u'locale':u'de',
               u'description':               u'Doppelrahmstufe\nAT Kasezubereitung 60% F.LT\nzutaten:Frischkase,
               2               gefriergetrockne\nter Gorgonzola,
               Salz,
               Verdickungsmittet\nJohannisbrotkernmehl und Guarkemmehlt\nAroma,
               Stickstoff zum Aufschlagen\nNach dem Offnen alsbald verzehren\nUngeoffnet gekuhlt mindestens\nhaltbar bis:siehe Boden\nBY 706\nIn Deutschland hergestellt\n',
               u'boundingPoly':{  
                  u'vertices':[  
                     {  
                        u'y':232,
                        u'x':190
                     },
                     {  
                        u'y':232,
                        u'x':1500
                     },
                     {  
                        u'y':1410,
                        u'x':1500
                     },
                     {  
                        u'y':1410,
                        u'x':190
                     }
                  ]
               }
            }
         ]
      }
   ]
}

What to do

TODO

• remove json with error messages
• move all the JSONs to production

Process

sudo nohup sh -c 'for f in $(find . -type f -regex ".*/[0-9].jpg*"); do sudo python /home/xxxxxxxx.py $f;done'
sudo nohup sh -c 'for f in $(find . -name 'nutrition.*.full.jpg' -type f); do sudo python /home/xxxxxxxx.py $f;done'
sudo nohup sh -c 'for f in $(find . -name 'front.*.full.jpg' -type f); do sudo python /home/xxxxxxxx.py $f;done'
sudo nohup sh -c 'for f in $(find . -name 'ingredients.*.full.jpg' -type f); do sudo python /home/xxxxxxxx.py $f;done'

Results

Number of images

46715+128832+59961+180420 = 415928(edited)

teolemon@ks3095298:/home/off/html/images/products$ ls -lR /home/off/html/images/products/ | find . -name 'nutrition.*.full.jpg' -type f | wc -l
46715
teolemon@ks3095298:/home/off/html/images/products$ ls -lR /home/off/html/images/products/ | find . -name 'front.*.full.jpg' -type f | wc -l
128382
teolemon@ks3095298:/home/off/html/images/products$ ls -lR /home/off/html/images/products/ | find . -name 'ingredients.*.full.jpg' -type f | wc -l
59961
teolemon@ks3095298:/home/off/html/images/products$ ls -lR /home/off/html/images/products/ | find . -type f -regex ".​​*/[0-9].jpg*​​" | wc -l
180420

Number of JSONs

ls -lR /home/off/html/images/products/ | find . -type f -regex ".​​*/[0-9].json*​​" | wc -l
415308

Versions of the same product

• All versions of images selected have been processed
• All images ever uploaded have been processed

Check complete products

• Check how similar ingredients lists are to what is detected
• Check if brands are suggested that are not here (eg Umbrella brands)
• Extract addresses
• Extract URLs

Suggest values for incomplete products

• Try to suggest possible categories based on extracted text
• Try to suggest brands, both based on the Brand JSON field and on Raw text extraction

Search engine (internal/external) considerations

• Add raw output as hidden text to enable search engine to index incomplete products
• Add hidden field to enable the internal search engine to find incomplete products

New fields to add ?

• Cooking recommandation
• Storage recommandation
• Description (some products are very talkative)
• Postal address of the producer
• Postal address of the distributor
• Email Address
• Phone number
• Website of the brand (vs product)
• Ingredient percentage