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

How to process images to generate JSONs

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'

How to check the 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

Number of files in the directory

teolemon@ns3362784:/home/off/html/images/products$ find . -type f | sed 's/.*\.//' | sort | uniq -c
   2514 front
     35 gif
     27 ingredients
2890282 jpg
 478982 json
      1 kxs2sl
      1 out
   3311 png
    210 tif
    153 txt

Versions of the same product

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

How we can leverage the data

Perform checks on products that are already complete

• Check how similar ingredients lists are to what is detected
• Check if brands are suggested that are not here (eg Umbrella brands)
• Extract cooking instructions
• Extract storage information
• Extract non-essential marketing information (eg on wines)
• Extract postal addresses
• Extract URLs

Suggest values for incomplete products

• Categories candidates, based on extracted text

• Brands candidates based on:
  • the Brand JSON field
  • Raw text extraction
  • URL regex
    • Based on Wikidata urls
    • Based on urls extracted in other products, or set as Product urls

• Packaging candidates
  • Taxonomy match
  • Existing values match

• Location candidates
  • OpenStreetMap/Wikidata match
  • Taxonomy match
  • Existing values match

• Packager codes candidates
  • EMB code
  • EU codes

• Quantity candidates
  • Regex match

• Labels, certifications, awards
  • Taxonomy match
  • Existing values match

• Origin of ingredients
  • Taxonomy match + Dropdown
  • Existing values match + Dropdown

• Manufacturing or processing places
  • OpenStreetMap/Wikidata match
  • Taxonomy match
  • Existing values match

• Link to the product page on the official site of the producer
  • Regex match
  • Google Search with name+brand

• Best before date
  • Regex match

• City, state and country where purchased
  • OpenStreetMap/Wikidata match
  • Taxonomy match
  • Existing values match

• Stores
  • Taxonomy match
  • Existing values match

• Countries where sold
  • OpenStreetMap/Wikidata match
  • Taxonomy match
  • Existing values match

• Ingredients list
  • Regex match
  • Taxonomy match
  • Existing values match

• Traces
  • Regex match
  • Taxonomy match
  • Existing values match

• Serving size
  • Regex match

• Nutrients volume
  • Regex match

• Ecological footprint
  • Regex match

Make uncomplete products searchable

• Add raw JSON output as hidden by default text to enable search engines to index incomplete products (it could be collapsed and shown after the click of a button)
• Add hidden field to enable the internal search engine to find incomplete products

Expand Open Food Facts coverage by adding additional information in new fields

• Description
  • some products are very talkative
  • it can be a first step before we add the other fields
• Cooking recommandation
• Storage recommandation
• Postal address of the producer
• Postal address of the distributor
• Email Address of the producer
• Email Address of the distributor
• Phone number of the producer
• Phone number of the distributor
• Website of the brand
• Ingredient percentage