« Ingedata is a crucial partner to fasten the time to market of our AI models. They act with a strong collaborative mindset. I was impressed by the way they onboarded a specialist team in Fashion, that was trained specifically using our previous work with the Institut Français de la Mode. »
Jaafar Bounaim CEO @Miroa
Fashion and footwear companies will be able to achieve unprecedented product customization and tap into more detailed consumer information. Through smart manufacturing, companies can focus on improving their internal operations and creating a more sustainable supply chain. Industry 4.0 will help move the global textile and apparel industry into a more sustainable era, improving energy efficiency, resource productivity and carbon footprint. It will be the driving force in building a greener future.
The concept of affordable mass customization is that manufacturers will one day be able to offer products with a range of features and options that allow consumers to essentially create their own item, without the long development times and high costs associated with traditional manufacturing methods.
Bounding Boxes is one of the most common segmentation techniques, as it outlines the shape of an object by defining its X and Y coordinates. They are fast to draw but might include some background that will lower the accuracy with which your model is detected.
Classification tags images with single or multiple labels, based on a list of classes that was previously consolidated with experts in the relevant field to ensure that your model fits its market.
Polygons are a very popular segmentation technique that accurately outlines a specific area of interest and exclude elements of background that would lower the performance of your Computer Vision model. While not as accurate as Semantic Segmentation, they are much faster to draw, making them a strong option to train your model with both accurate and high-volume annotations.
Bounding Boxes is one of the most common segmentation techniques, as it outlines the shape of an object by defining its X and Y coordinates. They are fast to draw but might include some background that will lower the accuracy with which your model is detected.
Classification tags images with single or multiple labels, based on a list of classes that was previously consolidated with experts in the relevant field to ensure that your model fits its market.
Polygons are a very popular segmentation technique that accurately outlines a specific area of interest and exclude elements of background that would lower the performance of your Computer Vision model. While not as accurate as Semantic Segmentation, they are much faster to draw, making them a strong option to train your model with both accurate and high-volume annotations.
We offer high-end services with our unique data production methodology and, more importantly, our wonderful team of 500. As a people company, Ingedata thrives on bringing talents from developing countries on the international AI scene.
One of the bases used for data annotation by our Fashion business experts is an ontology created by the 'Institut Français de la Mode'.
Understanding market trends to lead a luxury brand’s decisions on their future collections.
Learn more about our approach and explore our case studies
With more than 100 projects in the field of ML model training, we are recognized for our remarkable know-how in production management and our guarantee of quality.
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Externalizing your data can represent a significant risk in terms of loss, deterioration, or theft. At Ingedata, your projects are designed and carried out in-house, from our secure production centers.
Ingedata's annotators have degrees ranging from bachelor's to engineer's or doctorate in your field. All our teams work from our production centers and are trained in the specific requirements of preparing data for machine learning.
Accelerate the optimization of your algorithm by using data prepared specifically for you. We collect, enrich, and categorize your data to build your own datasets.
We fit seamlessly into your current production mode, take over any coordination and adapt our team to your specific constraints in terms of data volume and quality.
Proudly awarded as an official contributor to the reforestation project in Madagascar
(Bôndy - 2024)
