Input path: /home/debian/html/nutritwin/output_llm/6735e3127e9ea/input.json
Output path: /home/debian/html/nutritwin/output_llm/6735e3127e9ea/output.json
Input text:
DB path: __deriveddata__/DerivedObjects/Data/KcalMeDB_fr.sl3
Picto path: __deriveddata__/DerivedObjects/Data/PictoMatcherNetNG_fr.json
Sport grounding path: __deriveddata__/DerivedObjects/Data/DerivedSportMET.json
==================================================================================================================================
Prompt from user:
==================================================================================================================================
###########################################
# For image extraction, GPT4 is used #
###########################################
==================================== Prompt =============================================
In the image, identify all the foods and the beverages.
For each of them, identify the "name", the "type", the "quantity", if it exists, the "brand" and the "cooking" mode.
"Portions", like "tranche", are quantities.
Ignore what it is not connected to nutrition, beverage or food.
When the "brand" is not specified and the product is very well-known (like "Coca-Cola"), provide the brand name in "brand", otherwise set "brand" to "".
Identify what "type" of food.
Identify the "company" to which the "brand" belongs.
Estimate the "weight" in grams or centiliters for each result.
Identify the time is the current time, map it on the closest case: "petit-déjeuner", "déjeuner", "grignotage" or "dîner".
When the "name" has synonyms, use the most common name, example: "yaourt" is more common than "yogourt".
Format the result for each ingredient of food & beverage in french in JSON in an array of tuples {"name":, "quantity":, "weight":, "cooking":, "brand":, "company":, "type":, "time":, "event": "declaration"}.
=========================================================================================
Image recognition....
------------------------------ LLM Raw response -----------------------------
```json
[
{
"name": "oeufs brouillés",
"quantity": "portion",
"weight": "200",
"cooking": "brouillé",
"brand": "",
"company": "",
"type": "plat principal",
"time": "petit-déjeuner",
"event": "declaration"
},
{
"name": "jambon",
"quantity": "incorporé",
"weight": "30",
"cooking": "",
"brand": "",
"company": "",
"type": "viande",
"time": "petit-déjeuner",
"event": "declaration"
}
]
```
Note: The estimation of weight for the oeufs brouillés and the jambon is based on standard serving sizes and might not be precise. Weight is given in grams. No beverages are visible in this image, and the time for the meal (petit-déjeuner) is inferred based on the common timing of eating such foods.
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "oeufs brouillés",
"quantity": "portion",
"weight": "200",
"cooking": "brouillé",
"brand": "",
"company": "",
"type": "plat principal",
"time": "petit-déjeuner",
"event": "declaration"
},
{
"name": "jambon",
"quantity": "incorporé",
"weight": "30",
"cooking": "",
"brand": "",
"company": "",
"type": "viande",
"time": "petit-déjeuner",
"event": "declaration"
}
]
```
Note: The estimation of weight for the oeufs brouillés and the jambon is based on standard serving sizes and might not be precise. Weight is given in grams. No beverages are visible in this image, and the time for the meal (petit-déjeuner) is inferred based on the common timing of eating such foods.
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "oeufs brouillés", "quantity": "portion", "weight": "200", "cooking": "brouillé", "brand": "", "company": "", "type": "plat principal", "time": "petit-déjeuner", "event": "declaration" }, { "name": "jambon", "quantity": "incorporé", "weight": "30", "cooking": "", "brand": "", "company": "", "type": "viande", "time": "petit-déjeuner", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'oeufs brouillés', 'quantity': 'portion', 'weight': '200', 'cooking': 'brouillé', 'brand': '', 'company': '', 'type': 'plat principal', 'time': 'petit-déjeuner', 'event': 'declaration'}, {'name': 'jambon', 'quantity': 'incorporé', 'weight': '30', 'cooking': '', 'brand': '', 'company': '', 'type': 'viande', 'time': 'petit-déjeuner', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'oeufs brouillés', 'quantity': 'portion', 'weight': '200', 'cooking': 'brouillé', 'brand': '', 'company': '', 'type': 'plat principal', 'time': 'petit-déjeuner', 'event': 'declaration'}
First try:
SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% oeuf brouille %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Oeufs Brouillés - oeuf brouille - - - 5704 - - - KCA#e7821dbd6e4eed7e40207749566215c6
Oeufs Brouillés au Parme - oeuf brouille parme - - - 21 - - - KCA#46f4f89df78ef4f353027ad54bc58fb2
Oeufs Brouillés au Piment - oeuf brouille piment - - - 13 - - - KCA#206dad6382c9ccfc755dff2b1ea88b47
Oeufs Brouillés à la Bressane - oeuf brouille bressane - - - 7 - - - KCA#3977cd58d40def04a5618de6e2cfc76a
Croque Monsieur aux Oeufs Brouillés - croque monsieur au oeuf brouille - - - 3 - - - KCA#0d6d602aab5ed85a471d72a5fba11639
----------------------------------------------------
ERROR: no solution for picto in the first solution
----------- result to be analyzed -----------
{'name': 'jambon', 'quantity': 'incorporé', 'weight': '30', 'cooking': '', 'brand': '', 'company': '', 'type': 'viande', 'time': 'petit-déjeuner', 'event': 'declaration'}
First try:
SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% jambon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Jambon Cru - jambon cru - - - 9885 - - - CIQ#64b8482a5f9494f91650a6dfbb0cd41e
Jambon Sec - jambon sec - - - 0 - - - CIQ#96c8fe38103fc721a15cfe55d6e25c6f
Jambon Cru - jambon cru - fumé - - 268 - - - CIQ#5f3f73264b7c8e8500821bffaac09aee
Jambon Sec - jambon sec - découenné, dégraissé - - 293 - - - CIQ#25959c69f01c1f2120ccc677017fa727
Jambon Cru - jambon cru - fumé, allégé en matière grasse - - 0 - - - CIQ#f647a53f900ffb0f8b6bcc1b9daac3fd
Jambon Fumé - jambon fume - - - 1235 - - - KCA#b89a3b14af6277985c3d77e8a43fd3a7
Jambon Cuit - jambon cuit - fumé - - 130 - - - CIQ#17ca7e15b0319f1e287cbd0bcf02e149
Jambon Cuit - jambon cuit - choix - - 0 - - - CIQ#31a3ba17bd765304c35083900245a906
Jambon Cuit - jambon cuit - supérieur - - 879 - - - CIQ#62b09fb38df99e94d05d097272b0f943
Jambon Cuit - jambon cuit - choix, avec couenne - - 0 - - - CIQ#c197beb44fda0f03581cdd01ee751078
Jambon Cuit - jambon cuit - supérieur, découenné - - 0 - - - CIQ#a4feb0298e2ed9bf7086021f843d5542
Jambon Cuit - jambon cuit - supérieur, avec couenne - - 0 - - - CIQ#44f954aa2607fc98de99e42c7a2f34f0
Jambon Cuit - jambon cuit - choix, découenné dégraissé - - 0 - - - CIQ#1bdbfa77737e32f3afd8b85235c13da8
Jambon Cuit - jambon cuit - de Paris, découenné dégraissé - - 0 - - - CIQ#2204461860d60e77475581012d525590
Jambon Cuit - jambon cuit - supérieur, découenné dégraissé - - 0 - - - CIQ#7fe80de772280767444b552c0124ab0f
Jambon Cuit - jambon cuit - supérieur, à teneur réduite en sel - - 0 - - - CIQ#f6e3b7457066170ebc96fe96171fba23
Jambon Blanc - jambon blanc - - - 41088 - - - KCA#a2c3580fad4917288fe40406fb88cadb
Jambon Bayonne - jambon bayonne - - - 2108 - - - KCA#a7501ed926d61fc6282a9dc417593554
Jambon Persillé - jambon persille - - - 315 - - - KCA#a68e12a46f2795c6c267b411dd8111f4
Jambon de Poulet - jambon de poulet - - - 5421 - - - KCA#8a8c7fe60575ff37bd0a2f58c58a75a0
----------------------------------------------------
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': '', 'intents': ['Identify food in an image'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Oeufs Brouillés', 'normName': ' oeuf brouille ', 'comment': '', 'normComment': '', 'rank': 5704, 'id': 'KCA#e7821dbd6e4eed7e40207749566215c6', 'quantity': 'portion', 'quantityLem': 'portion', 'pack': ['OE2.w60', 'OEU.w60'], 'type': 'plat principal', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'petit-déjeuner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Jambon Cru', 'normName': ' jambon cru ', 'comment': '', 'normComment': '', 'rank': 9885, 'id': 'CIQ#64b8482a5f9494f91650a6dfbb0cd41e', 'quantity': 'incorporé', 'quantityLem': 'incorpore', 'pack': ['TR3.w25'], 'type': 'viande', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'petit-déjeuner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 7.1021339893341064}
----------------------------------------------------------------------------------
LLM CPU Time: 7.1021339893341064