Retail and commerce

AI is widely used in retail personalizing the customer experience and making business processes automated
Tagias does professional image annotation in retail and labels any objects on the pictures: brands, items, logos, consumers, prices, barcodes, etc. We do image annotation and tagging in all the retail industries – furniture, clothing, appliances, food, products, cosmetics, accessories,
and others.

We annotate objects on images in order to train apps to recognize them for machine learning. Our team has the expertise and can label images accurately, you receive a high-quality annotated dataset. We do manual human annotation and visual inspection as well in order to give you a professionally labeled dataset to train your data for creating an AI model for the retail industry.
Tagias Manager helps you create a good technical task for the data or markup that needs to be performed. So that you get a training dataset that gives real results and a low error rate.
RETAIL
CASES

Use cases

Image annotation

Using data to learn patterns, preferences in order to analyze and predict shopping behavior

Collecting, tagging, and labeling products' barcodes, set numbers trains AI to recognize them accurately
Shelves optimization
Customer behavior
Items' labels
Shelves optimization
Customer behavior
Items'
labels
Training AI by monitoring grocery shelves allows detecting the type of products for optimizing assortment and placement

Bounding boxes
Classification
Keypoints
Polygons
Lines
Semantic segmentation
Bounding box annotation
Bounding boxes
The most common type of data annotation. Bounding boxes are mainly intended to detect objects, delineating their borders with transparent rectangles. Bounding boxes are applied in almost all industries of the data labelling market.
Images classification
Classification
This method is used to determine the presence of an object in the image. A specific label is assigned to each image. Image tagging helps train AI to recognize objects' classes.
Keypoints annotation
Keypoints
This type of annotation uses dots across an image to identify an object or its details/parts. Keypoints are applied mostly with facial recognition, body parts, and postures.
Polygons annotation
Polygons
Polygons are used to determine an object's shape and location with maximum precision while avoiding additional noise. Polygon annotation is applied in almost all industries.
Lines annotation
Lines
Lines annotation is used for detecting and recognizing lanes. This type of annotation is applied mostly in the automotive industry to make self-driving cars safe.
Semantic segmentation
Semantic segmentation
A data labelling method where objects are delineated in the image at the pixel level, depending on class. It's called semantic segmentation because each pixel has semantic meaning. Segmentation is usually applied in the automotive industry.