Ingredients image dataset. Jan 1, 2021 · Marin et al.

Ingredients image dataset You can see the explore the serving sizes, time required to prepare a dish, most common ingredients, different cuisines, diets, courses and what not. This dataset consists of images of Indian food. In this paper, we present the introduction of INDoRI (Indian Dataset of Recipes and Ingredients), a compilation drawn from seven distinct online platforms, representing 18 regions within the Indian subcontinent. json images/ images/train images/val images/test AIFood dataset includes 24 categories and totally 372,095 food images around the world. For the ingredients, we web scraped Food image dataset containing 1453 images: Food image analysis: Kawano and Yanai : 2014: Color, HoG and Fisher Vector: UECFOOD-256 food image dataset: Real-time food image recognition: Oliveira et al. How- Feb 21, 2024 · In this paper, we present the introduction of INDoRI (Indian Dataset of Recipes and Ingredients), a compilation drawn from seven distinct online platforms, representing 18 regions within the Oct 21, 2021 · To the best of our knowledge, the IIITD CulinaryDB dataset is the only dataset with a mapping of ingredients to dishes, but it lacks images. To address this complexity, we used the datasets from multiple sources. There are other larger datasets like Recipe1M+ and Food101 but they do not index high on Indian dishes. FoodSeg103 is a new food image dataset containing 7,118 images. kaggle. 1(b)), and thus, there is limited work on multi-class classification of food ingredient images in the literature Ingredients: Complete ingredient lists, ensuring transparency about product composition. I. 70 datasets • 152538 papers with code. 01256, 2019. Jan 10, 2022 · In this paper, we introduce a new recipe dataset MIRecipe (Multimedia-Instructional Recipe). 2 Multi-ingredient food image dataset (MIFI) This dataset is used to evaluate the performance of multiple ingredient recognition in food images. While the RecipeNLG dataset is based on the Recipe1M+ dataset, it greatly expands the number of recipes available. Oct 1, 2019 · Furthermore, the dataset is designed to link to an existing recipe corpus and thus, a variety of recipe texts, such as the title, description, ingredients, and process, is available for each image. Hamarneh, "Visual Diagnosis of Dermatological Disorders: Human and Machine Performance", arXiv pre-print arXiv:1906. To reduce sparsity of the ingredient features and make use of ingredient information in the ingredient dictionary dataset we obtained, we used the SequenceMatcher to find match of all ingredients to the 1750 ingredients in the ingredient dataframe. Both visible and non visible ingredients (statistics involved here). here if you are not automatically redirected With the goal of producing image encodings for every image in our dataset, we ran the Recipe 1M training data through a variety of convolutional neural networks, ResNet-50, ResNet-101, and DenseNet-121, each trained on the ImageNet dataset. , 2017). Dataset Card for Indian Foods Dataset Dataset Summary This is a multi-category(multi-class classification) related Indian food dataset showcasing The-massive-Indian-Food-Dataset. By using EfficientNet-B0 for transfer learning, the model achieves high accuracy in classifying food images and retrieving relevant recipes and ingredients. Here are a few use cases for this project: Meal Preparation: Users can leverages the "Food Ingredients Image Detection_Team4" model to facilitate their meal preparations, helping them identify specific ingredients on their kitchen counters or in their pantry. 48% on test dish image dataset. 81% on test set of segment-based ingredients dataset. Jan 1, 2021 · Marin et al. Jun 23, 2024 · • Criterion 5: Studies in which the dataset is available on the web. In the dataset, several images of different lines of food products have been acquired to create a harmonized dataset. I did this experiment 2 weeks ago because a collage built a dataset of images tagged with the ingredients. Consumer Education: Create tools and applications that help consumers understand the ingredients in their cosmetics, enabling them to make more informed choices. An ingredient dataset containing image 12,558 images across 15 food ingredient classes with augmentation 3. json) to YOLO format (. Mar 13, 2024 · Abstract. Existing food image segmentation models are underperforming due to two reasons: (1) there is a lack of high quality food image datasets with fine-grained ingredient labels and pixel-wise location masks -- the existing datasets either carry Apr 10, 2024 · The single-ingredient image dataset, designed in accordance with the “New Food Ingredients List FOODS 2021”, encompasses 9,982 images across 110 diverse categories, emphasizing variety in Dec 14, 2021 · After combining and cleaning the image data to limit it to the 75 most common ingredients, the dataset consisted of 14,919 images. Compared with existing food recognition datasets, Food2K bypasses them in both categories and images by one order of magnitude, and thus establishes a new challenging benchmark to develop advanced models for food visual representation learning. Preprocess the images by resizing them to a uniform size, applying normalization to ensure consistent lighting and color, and augmenting the dataset to increase diversity and robustness. It contains a total of 3,213 unique ingredients (10 per recipe on average) and a Jan 26, 2024 · The single-ingredient image dataset, designed in accordance with the book entitled "New Food Ingredients List FOODS 2021", encompasses 9982 images across 110 diverse categories, emphasizing variety in ingredient shapes. Ingredients (v3, 2024-03-22 3:31pm), created by Ingredients Sep 19, 2023 · The endeavor becomes more accessible with the availability of a well-organized dataset. Food Ingredients Image Detection_Team4 (v1, 2023-07-20 12:58pm), created by DSStudy Jul 9, 2019 · In addition to teaching food images and ingredients, J. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. Index Terms—Automated diet assessment, deep learning, visual ingredients recognition, machine learning, multi-label learning. [5] proposed Recipe1M+ dataset, a large-scale, structured corpus of over one million cooking recipes (including cooking instructions and ingredients) and 13 million food images. To train the food detection model, we survey the following datasets: Open Images V6-Food: Open Images V6 is a huge dataset from Google for Computer Vision tasks. Supported Tasks and Leaderboards [More Information Needed] Languages English. The input image to the ResNet-50 model is of size 256*256 with 3 slices of RGB image taken from both datasets. Recipes5k: Dataset for ingredients recognition with 4,826 unique recipes composed of an image and the corresponding list of ingredients. g. Images: High-quality product images. A search was conducted using the IEEE Xplore [11], Scopus [12], and ACM Digital Library [13] databases. Hence we prepare an Indian food focused dataset with images. Go to Universe Home In this paper, we introduce a large-scale food images dataset namely AIFood, which is constructed to aim ingredient recognition in food image research. Convolution Neural Network (CNN) model was used to identify food ingredients, and for recipe 3. I dropped the images and created the simplified resources in this repo. In this paper, we propose a new framework for ingredient segmentation MIRecipe is a dataset containing images for every cooking step while other recipe datasets provide images only for a part of steps or only provide the finished dish image. The most extensive recipe datasets are Recipe1M+ Marín et al. Our dataset consists of over 120,000 images and 5000 ingredient types. Instructions: Instructions to recreate the dish. AIFood dataset includes 24 categories and totally 372,095 food images around the world. Project Description. 2014: Color, Texture: Images were gathered using mobile’s camera: Mobile Food Recognition: Pouladzadeh et al. Keywords: Food image dataset, calorie measurement, food detection. Ingredient Analysis: Researchers and developers can use this dataset to analyze trends in cosmetic ingredients, identify common allergens, or study the effectiveness of certain components. Additional 180 test images have been manually labelled with Roboflow Extract files somewhere (we refer to this path as path_to_dataset). The ingredient image dataset is sourced from Roboflow, a popular platform for preparing datasets and deploying ML models. MIFI dataset contains a total of 2121 images. Therefore, a search for alternative datasets was conducted, and the “Fruits and Vegetables Image Recognition Dataset,” available on the Kaggle 4479 open source Objects images and annotations in multiple formats for training computer vision models. Recipe 1M+, ETH Food-101 [ 2 ], and some other datasets contain a large number of images, but Haodou, from which we collect data, has a far larger number of recipes so our If you find this code useful, please consider citing: @inproceedings{salvador2017learning, title={Learning Cross-modal Embeddings for Cooking Recipes and Food Images}, author={Salvador, Amaia and Hynes, Nicholas and Aytar, Yusuf and Marin, Javier and Ofli, Ferda and Weber, Ingmar and Torralba Use Recipe Ingredients to Categorize the Cuisine. May 12, 2021 · To enable precise fine-grained food image segmentation, the authors have developed a comprehensive dataset known as FoodSeg103. lactic acid The Food Preparation & Cooking Collection dataset offers a comprehensive exploration of the culinary world, capturing the artistry and passion behind the preparation and cooking of delectable dishes. scraped from Google. Images are annotated with 104 ingredient classes and each image has an average of 6 ingredient labels and pixel-wise masks. We ensure that 5-10 samples with similar 4196 open source FOOD-INGREDIENTS images plus a pre-trained FOOD-INGREDIENTS dataset model and API. [2021] and Oct 1, 2023 · This dataset combines images from existing datasets with images of food on the web. }, year = {2019} } @inproceedings 4196 open source FOOD-INGREDIENTS images plus a pre-trained FOOD-INGREDIENTS dataset model and API. Available recipe datasets are mainly focused on information retrieval (mainly visual or cross-modal), image-text recipe generation, or extracting general information about cooking and ingredients. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This provides overall satisfactory matching results with mistakes occasionally (e. Food-101 dataset consists of images of food, organized by the type of food into 101 categories. Project Comparing Cosmetics by Ingredients. Min et al. Each database contains a "recipes" table with the following three columns: Title: Title of the dish. Each image contains multiple ingredients. 1, JANUARY 2021 187 Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images Javier Mar ın , Aritro Biswas, Ferda Ofli , Senior Member, IEEE, Nicholas Hynes, Amaia Salvador, Yusuf Aytar, Ingmar Weber , Senior Member, IEEE, and Antonio Torralba Abstract—In this paper, we introduce . It consists of wide variety of dish images taken accross India. Buying new cosmetic products is difficult. This dataset encompasses 7,118 images of Western cuisine, meticulously annotated with 103 distinct ingredient classes along with their corresponding segmentation masks. For each class, 250 manually reviewed test images are provided as well as 750 training images. The rst The multi-modal aspect of recipes has shown promise in enhancing cooking procedure understanding [40] by using auxiliary data such as video [22,30] or images [27,42]. In this paper, we propose a new approach to segment ingredients by utilizing a CNN-based Single-Ingredient Classification Model. These images would be all resized to 224x224 and used to train 4196 open source FOOD-INGREDIENTS images and annotations in multiple formats for training computer vision models. com Click here if you are not automatically redirected after 5 seconds. The new dataset provides over 1 million new, preprocessed and deduplicated recipes on top of the Recipe1M+ dataset. Each row in these two files consists of the path to an image and its fine-grained label followed by its coarse-grained label, where both labels are represented as integers. chicken can be substituted with tofu/paneer) Image Captioning and Recipe Matching on Food Image Dataset with Deep Learning Kaylie Zhu Abstract Harry Sha* I Chenlin Meng et al. ingredients_images_for_detection dataset by Groceryitemsdetection. Our dataset contains, for every dish its Jun 1, 2024 · The MResNet-50 model is trained using ImageNet and the weights are reused for classifying images in Food-101, and UECFOOD256 datasets. Ingredients (v3, raw-images), created by Food 1) Construct the ingredients co-occurrence matrix based on a large-scale dataset which contains multi-label information of each data sample; 2) Predict salient ingredient from food image by salient ingredients classifier and use salient ingredient as a reference to search co-occurrence ingredients from co-occurrence matrix and rank these Jan 1, 2024 · We aim to develop an application that automatically creates a nutrition facts label from food images for precise dietary control. In detail, we firstly introduce a standardized biological-based hierarchical ingredient structure and construct a single-ingredient image dataset based on this Word2Vec fine-tuned on this dataset (ingredient2vec) to find similar ingredients (ingredients which have high cosine similarity) which could be used to recommend substitute ingredients - an additional check from the dataset if it is vegan would make it a vegan substitute recommendation (e. txt and test. Based evaluation. txt, val. The author compiled a dataset of 800,000 images of food and a corpus of 9975 open source grodery-store-items images. This comes mostly in the form of intense colors and sometimes wrong labels. CLIP [35] mod-ified GPT-2 [36] to obtain text features from textual input and used image-text contrastive learning, which trained the model with the similarity between the image and text. Ingredients: Ingredients as they were scraped from the website. This opens up many possibilities for machine learning enthusiasts and researchers. 3. ingredients detection, using a challenging dataset, Nutrition5K, and establish a strong baseline for future explorations. txt in the folder dataset includes the paths to the images in the training, validation and test set respectively. csv) contains a list of all ingredients covered in the dataset's dishes, their unique IDs, and per-gram nutritional information sourced from the USDA Food and Nutrient Database. The files train. 170 open source Ingredients images plus a pre-trained Recipe Ingredients model and API. PDF Abstract Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Created by Food recipe ingredient images Existing food image segmentation models are underperforming due to two reasons: (1) there is a lack of high quality food image datasets with fine-grained ingredient labels and pixel-wise location masks---the existing datasets either carry coarse ingredient labels or are small in size; and (2) the complex appearance of food makes it difficult to We make public the lists of ingredients together with the train/val/test split applied to the images from the Food101 dataset. Dataset Features Dataset size : 5000+ Captured by : Over 800+ crowdsource contributors Resolution : 99% images HD and above (1920x1080 and above Checking your browser before accessing www. Furthermore, we prove that a model trained with a high variability of recipes and ingredients is able to generalize better on new data, and visualize how it specializes each of its neurons to different ingredients. Computer Vision Lab is a research team equipped with artificial intelligence-based technologies for recognizing the 3D structure of objects and generating images. Jan 22, 2024 · To achieve the objective, the ingredients dataset has generated by extracting text from images containing ingredient lists of different ready-to-eat food products. Food2K is a large food recognition dataset with 2,000 categories and over 1 million images. 2015: Color, Texture, Size, Shape dients dataset and 82. It contains a total of 3,213 unique ingredients (10 per recipe on average) and a simplified version of 1,013 ingredients. dish name or ingredient information. View Version. The food images are relabeled using 24 categories. This dataset contains 16,643 images, of which 9866 images are training sets, 3430 images are validation sets, and the remaining 3347 images are test May 12, 2021 · Food image segmentation is a critical and indispensible task for developing health-related applications such as estimating food calories and nutrients. Detecting food ingredients for YOLOv5 (v2, 2023-02-13 6:08pm), created by Dataset for YOLO Mar 22, 2024 · 3186 open source produce images and annotations in multiple formats for training computer vision models. txt based) All images that do not contain any fruits or images have been removed, resulting in 8221 images and 63 classes (6721train, 1500 validation). json layer1. Two primary datasets are acquired: one comprising ingredient images and another containing textual recipe data. We collect food images from eight existing food image datasets and a food website. Each image is labeled with the corresponding food category. Pattern Anal. 1187 open source food-ingredients images and annotations in multiple formats for training computer vision models. Brand and Manufacturer Information: Details of the brand and manufacturer. Open Food Facts Images on AWS Open Dataset: The Ultimate Food Image Dataset Image by Mika Ruusunen (@mikafinland) Hello everyone! We’re very excited to announce that Open Food Facts Images is now available on AWS Open Dataset. contributed to collecting a dataset called Recipe1M. To solve our problem, we extracted from a large dataset on food related labels. Marin et al. It is the first HSI-based food image dataset, of which all images are labelled with dish-level and ingredient-level annotations and corresponding pixel-wise ingredient masks. 96% on test dish image dataset. In this paper, we introduce a large-scale food images dataset namely AIFood Nov 23, 2022 · This dataset consists of 101 food categories, with 101'000 images. The Indian Food Recipes dataset comprises 6871 entries sourced from Archana's Kitchen, offering detailed information on recipes, ingredients, cooking times, servings, cuisines, courses, and dietary preferences, facilitating culinary exploration. Next, we birth of large image-text datasets [13,58]. More details about some of these datasets can be found in our surveys: J. Detection of food ingredients from their image is a key process in calorie measurement systems used Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. AL-BEF [22] utilized ViT (pre-trained on large amounts of data and transferred to multiple mid-sized or small Mar 18, 2024 · This dataset contains 185,628 images of 208 food categories covering most of popular Chinese food, and these images include web images and photos taken in real world under unconstrained conditions. With our entire dataset encoded through the various CNNs, next came processing the user input. We ensure that 5-10 samples with similar Citation @article{marin2019learning, title = {Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images}, author = {Marin, Javier and Biswas, Aritro and Ofli, Ferda and Hynes, Nicholas and Salvador, Amaia and Aytar, Yusuf and Weber, Ingmar and Torralba, Antonio}, journal = {{IEEE} Trans. Aug 11, 2023 · It is important for food recognition to separate each ingredient within a food image at the pixel level. Keywords 16643 food images grouped in 11 major food categories Currently, there are very few food ingredients datasets available (as shown in Fig. Mar 6, 2024 · Acquire a large dataset of ingredient images with corresponding labels denoting the ingredients present in each image. This card has been generated using this raw template. Furthermore, Segment-based classifier achieves 94. 1 Introduction Food images, taken by people using their smartphones, are used in many proposed systems for food recognition, detection, and classification. The extracted set includes 18 labels with more than 20,000 images. The search terms used were “Dataset” AND “Image” AND Jul 9, 2023 · One popular dataset is the Food-101 dataset, which consists of 101 food categories with a total of 101,000 images. Kawahara, G. This dataset is invaluable for: RecipeNet leverages the Recipe1M, Recipe5K, and Ingredients 101 datasets to create a robust food classification and recipe retrieval system. It can even be scary for those who have sensitive skin and are prone to skin trouble. Flexible Data Ingestion. Food ingredients (v1, 2022-01-12 11:35pm), created by seongmin 3289 open source food images and annotations in multiple formats for training computer vision models. , featuring cooking videos and accompanying recipes; and the extensive “Recipe1M” dataset containing both recipes and images, brought forth by Salvador et Structure-Aware Generation Network for Recipe Generation from Images. This is a collection of datasets used for skin image analysis research. It provides a diverse and rich tapestry of images, showcasing the unique techniques, ingredients, and moments that define the culinary experience. It has both text and image data for every cooking step, while the conventional recipe datasets only contain final dish images, and/or images only for some of the steps. [17] finds a joint embed-ding of recipes and images for the image-recipe retrieval task. com and Recipe1M+ are the primary sources. Introduction Dataset consists of images of Indian food captured using mobile phones in a real-world scenario. Explore Popular Topics Like Government, Sports, Medicine, Fintech, Food, More. For each class, the images in the dataset contain a wide variety of ingredients to make training more difficult. The contents of path_to_dataset should be the following: det_ingrs. Feb 8, 2023 · In the present work, a new food image dataset HSIFoodIngr-64 containing 3,389 pairs of HSI and RGB images with 21 dish classes and 64 ingredient categories was established. 1 Single ingredient image dataset(SI110) We collect image samples of individual ingredients, aiming to capture a diverse range of shapes. Dataset Card for RecipeNLG Dataset Summary RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation. [12] expands the dataset Recipe1M[17] from 800k images to 13M. However, preparing such datasets is exceedingly hard and time-consuming. This dataset was built for free as part of the “AI Dataset Sponsorship Program” organized by Datumo, in collaboration with Computer Vision Lab. We made a custom dataset consisting of 9856 images belonging to 32 different food ingredients classes. In addition, a multi-ingredient image dataset is developed to rigorously evaluate the performance of our approach. Most existing research has trained a segmentation network on datasets with pixel-level annotations to achieve food ingredient segmentation. 9899 open source ingredients images and annotations in multiple formats for training computer vision models. Created by VegetableImages { Recipe Ingredients Dataset }, type = { Open Feb 21, 2024 · These are: a recipe question-answering dataset by Semih et al. Learn more. hwang1996/SGN • • ECCV 2020 We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task. No changes have been made to the text content. Jan 26, 2024 · The single-ingredient image dataset, designed in accordance with the book entitled "New Food Ingredients List FOODS 2021", encompasses 9982 images across 110 diverse categories, emphasizing variety in ingredient shapes. FOOD-INGREDIENTS dataset (v3, 2023-10-06 6:20pm), created by Food recipe ingredient images Citation @article{marin2019learning, title = {Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images}, author = {Marin, Javier and Biswas, Aritro and Ofli, Ferda and Hynes, Nicholas and Salvador, Amaia and Aytar, Yusuf and Weber, Ingmar and Torralba, Antonio}, journal = {{IEEE} Trans. It's provided as a large-scale benchmark for food image segmentation. Recipes5k: Dataset for ingredients recognition with 4,826 unique recipes composed of an image and the corresponding list of ingredients. The ingredient metadata CSV (metadata/ingredient_metadata. •Recipe 1M+, ETH Food-101 [2], and some other datasets contain a large number of images, but Haodou, from which we collect data, has a far larger number of recipes so our Trained On: food-ingredients-dataset 9780 Images. As the largest publicly available collection of recipe data, Recipe1M + affords the ability to train high-capacity models on aligned, multimodal data. json layer2. We preliminarily label each image using existing food information, e. 6 million recipes accompanied by images. The dataset has been converted from COCO format (. This dataset can be used for recoginition, fine Jul 19, 2017 · Taking profit of the joint images-text embedding explained here I have built a pipeline that recognizes ingredients in cooked food images. Kaggle uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. Two examples are shown in Figure 4. Mach. In this paper, we introduce Recipe1M +, a new large-scale, structured corpus of over one million cooking recipes and 13 million food images. - nileshely/Indian-Food Jul 27, 2017 · We make public two new datasets suitable for this purpose. In this context, we introduce our food recognition algorithm ChefNet, which studies the in- gredients and cooking procedure of given food images and thereby matches given food images to their respec- The dataset can be used to answer a lot of questions related to Food Recipes. Customer Ratings and Reviews: User-generated content for understanding product popularity and performance. We preliminarily label food ingredients recognition and designed an algorithm for recommending recipes based on recognized ingredients. The distribution of how many ingredients is included in each image is shown Oct 1, 2019 · A large-scale food images dataset namely AIFood is introduced, which is constructed to aim ingredient recognition in food image research, and applies preprocessing method which contains automatic white balancing and contrast limited adaptive histogram equalization methods to improve visual quality of food images. INTRODUCTION hat we eat and drink has a huge impact on our daily lives and our wellbeing. For instance, our dataset includes images of eggs in various forms such as boiled, scrambled, and fried, shown in Figure 2. Model Selection and Training Cross-Modal Retrieval is given an image, retrieving its recipe from a collection of test recipes or the other direction: retrieving the corresponding image given a recipe. The search terms we used were ‘Dataset’ AND ‘Image’ AND (‘Dish arranged’ OR ‘Ingredient’). Intell. Created by Food recipe ingredient images Aug 14, 2023 · It is important for food recognition to separate each ingredient within a food image at the pixel level. 43, NO. }, year = {2019} } @inproceedings This dataset is an extremely challenging set of over 5000+ original India food images captured and crowdsourced from over 800+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs. 0 Object Detection (Fast) Checkpoint: food-ingredients-dataset/2 . Jul 5, 2023 · Despite this, the dataset is extensive, with around 101,000 images that mostly contain images of prepared recipes, which do not align with the project’s main objective of using simple ingredients. To the best of our knowledge, ChineseFoodNet is the largest and most comprehensive dataset for visual Chinese food recognition. Model Type: Roboflow 3. Firstly, we constructed a new dataset with food category labels and a list of ingredients in a nutritionally calculable format using an image classification model and BERT for 1. I hope this dataset helps the Analytics community. Dataset Structure •MIRecipe is a dataset containing images for every cooking step while other recipe datasets provide images only for a part of steps or only provide the finished dish image. , comprising approximately 36k questions that users can query against the dataset; Epic Kitchen, introduced by Damen et al. Recipe1M+ is a dataset which contains one million structured cooking recipes with 13M associated images. Images were captured under wide variety of indoor lighting conditions. [2019] survey existing benchmark food datasets and challenges. Food-101, allrecipes. Salient ingredients n-ide tifiers predict remained ingredients and achieve mean accuracy of85. It consists of 26,725 recipes, which include 239,973 steps in total. vbbv aqspl hlwjfm llxp sgagqjlf fjncsvi pjqjkxb ytycpk nzruqeg dqyt