Computer vision-based solutions deliver the intelligence to simplify processes, drive new efficiencies, and empower faster decision-making. However, the inability to run real-time inference, high false alarms due to low model accuracy, and the failure to deploy on CPUs or edge devices are just some of the barriers to production faced by AI teams in manufacturing companies today.
Watch a compilation of clips demonstrating how you can use Deci in a variety of manufacturing use cases.
Amir Bar, Head of SW and Algorithm
The Deci platform is used by data scientists and machine learning engineers to build, optimize, and deploy highly accurate and efficient models to production. Teams can easily develop production grade models and gain unparalleled accuracy and speed tailored for any performance targets and hardware environment. Deci is powered by AutoNAC (Automated Neural Architecture Construction), the most advanced and commercially scalable Neural Architecture Search engine in the market. AutoNAC performs a multi-constraints search to find the architecture that delivers the highest accuracy for any performance targets and hardware environment.
from transformers import AutoFeatureExtractor, AutoModelForImageClassification
extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")
model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")