PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data
Peruvian cuisine has won numerous international awards, attracting tourists from around the world to Peru to experience its diverse culinary offerings. However, some dishes contain ingredients that can trigger allergic reactions, posing a potential health risk for visitors. To address this, we creat...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925003361 |
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| author | María Franchesca Arzola Gutierrez Edgar Alexander Canchari Muñoz Edwin Jonathan Escobedo Cárdenas |
| author_facet | María Franchesca Arzola Gutierrez Edgar Alexander Canchari Muñoz Edwin Jonathan Escobedo Cárdenas |
| author_sort | María Franchesca Arzola Gutierrez |
| collection | DOAJ |
| description | Peruvian cuisine has won numerous international awards, attracting tourists from around the world to Peru to experience its diverse culinary offerings. However, some dishes contain ingredients that can trigger allergic reactions, posing a potential health risk for visitors. To address this, we created PeruFoodNet, a dataset featuring 4,000 images of traditional Peruvian dishes. The dataset includes 40 of the most popular dishes, such as Ceviche and Anticuchos, with 100 images of each dish. The images of the dishes have been captured from various angles, settings, lighting conditions, dimensions and backgrounds. To gather these images, we prepared the dishes ourselves, purchased some from restaurants, and received contributions from external users over a two-month period. However, most of the images were captured by the authors of the dataset. The dataset is publicly available and can be valuable for research in image recognition and classification using Computer Science techniques, such as Deep Learning. Additionally, it can aid in identifying allergenic ingredients in dishes by linking the dish’s image to a list of ingredients through a technological platform, such as a chatbot or an app. |
| format | Article |
| id | doaj-art-badfc704f9ca47a8bf0d63d55ae27ff0 |
| institution | DOAJ |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-badfc704f9ca47a8bf0d63d55ae27ff02025-08-20T03:10:29ZengElsevierData in Brief2352-34092025-06-016011160410.1016/j.dib.2025.111604PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley DataMaría Franchesca Arzola Gutierrez0Edgar Alexander Canchari Muñoz1Edwin Jonathan Escobedo Cárdenas2Corresponding author.; Carrera de Ingeniería de Sistemas, Facultad de Ingeniería, Universidad de Lima. Av. Javier Prado Este 4600, Santiago de Surco 15023, PerúCarrera de Ingeniería de Sistemas, Facultad de Ingeniería, Universidad de Lima. Av. Javier Prado Este 4600, Santiago de Surco 15023, PerúCarrera de Ingeniería de Sistemas, Facultad de Ingeniería, Universidad de Lima. Av. Javier Prado Este 4600, Santiago de Surco 15023, PerúPeruvian cuisine has won numerous international awards, attracting tourists from around the world to Peru to experience its diverse culinary offerings. However, some dishes contain ingredients that can trigger allergic reactions, posing a potential health risk for visitors. To address this, we created PeruFoodNet, a dataset featuring 4,000 images of traditional Peruvian dishes. The dataset includes 40 of the most popular dishes, such as Ceviche and Anticuchos, with 100 images of each dish. The images of the dishes have been captured from various angles, settings, lighting conditions, dimensions and backgrounds. To gather these images, we prepared the dishes ourselves, purchased some from restaurants, and received contributions from external users over a two-month period. However, most of the images were captured by the authors of the dataset. The dataset is publicly available and can be valuable for research in image recognition and classification using Computer Science techniques, such as Deep Learning. Additionally, it can aid in identifying allergenic ingredients in dishes by linking the dish’s image to a list of ingredients through a technological platform, such as a chatbot or an app.http://www.sciencedirect.com/science/article/pii/S2352340925003361GastronomyFood allergensFood classificationVisual computingDeep learning |
| spellingShingle | María Franchesca Arzola Gutierrez Edgar Alexander Canchari Muñoz Edwin Jonathan Escobedo Cárdenas PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data Data in Brief Gastronomy Food allergens Food classification Visual computing Deep learning |
| title | PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data |
| title_full | PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data |
| title_fullStr | PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data |
| title_full_unstemmed | PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data |
| title_short | PeruFoodNet: A unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferenceMendeley Data |
| title_sort | perufoodnet a unique dataset of traditional peruvian food for image recognition systems and allergenic ingredient inferencemendeley data |
| topic | Gastronomy Food allergens Food classification Visual computing Deep learning |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925003361 |
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