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[[Category:Robotoff]]
 
== Finding opportunities ==
 
== Finding opportunities ==
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=== Option 1 ===
 
# Download the OCR JSONL
 
# Download the OCR JSONL
# <pre>grep -o '\<WORD\>' | wc -l</pre>
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# <pre>zgrep -n '05.01.07' FILE    | wc -l</pre>
== Using REGEXes ==
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=== Option 2 ===
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# Right click on an image in a product page, in edit mode (eg 1.jpg)
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# Replace `.jpg` by `.json`
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# Find patterns or `logoAnnotations` in the JSON
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== Adding detections using REGEXes ==
 
https://github.com/openfoodfacts/robotoff/tree/master/robotoff/insights/ocr
 
https://github.com/openfoodfacts/robotoff/tree/master/robotoff/insights/ocr
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</pre>
 
</pre>
   −
== Add the function to the processing pipeline to plug it to Robotoff ==
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=== Add the function to the processing pipeline to plug it to Robotoff ===
 
This happens in the same file.
 
This happens in the same file.
 
<pre>
 
<pre>
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</pre>
 
</pre>
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== Grab yourself a sandwich ==
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=== Grab yourself a sandwich ===
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== Using Flashtext ==
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== Adding detections using Flashtext ==
 
https://github.com/openfoodfacts/robotoff/tree/master/data/ocr
 
https://github.com/openfoodfacts/robotoff/tree/master/data/ocr
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=== Expanding existing detections ===
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* Choose a file matching the detection you want to add
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In this example: https://github.com/openfoodfacts/robotoff/blob/master/data/ocr/brand_logo_annotation.txt
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* Add entries one per line. The raw `logoAnnotation` you find in the OCR JSON is on the left, the value you want to add in the brand field is on the right.
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<pre>
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alnatura||Alnatura
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Andros France||Andros
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andros||Andros
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</pre>
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=== Add a new type of detection ===
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* Create a file `fishing_flashtext.txt` and add one value to extract per line
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=== Add it to the Robotoff settings ===
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<pre>
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robotoff/settings.py
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OCR_LABEL_WHITELIST_DATA_PATH = OCR_DATA_DIR / "label_whitelist.txt"
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OCR_FISHING_FLASHTEXT_DATA_PATH = OCR_DATA_DIR / "fishing_flashtext.txt"
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</pre>
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=== Plug it into the OCR pipeline ===
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<pre>
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robotoff/insights/ocr/packager_code.py
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    codes = text_file_iter(settings.OCR_FISHING_FLASHTEXT_DATA_PATH)
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    return generate_keyword_processor(("{}||{}".format(c.upper(), c) for c in codes))
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</pre>

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