Automated deduplication of images
We understand that different media collections have distinct requirements for image uniqueness and similarity. That’s why our API enables you to choose models that align with your specific needs, ensuring only relevant near-duplicates are identified. For instance, a digital art archive may have a different tolerance for similarity compared to a retail product image database.
Leveraging the power of neural network-generated embeddings, our deduplication process transcends traditional SHA1 hash comparisons, which only catch exact duplicates. Our method unveils near-duplicates and similar images, a vital capability for diverse domains like digital marketing, where variant images of a product may exist, or in historical archives, where slightly different versions of photo may hold significant value.
The images below showcase various configurations, demonstrating our system’s adaptability across use cases. Your deduplication settings can be tailored to match your industry’s standards seamlessly, aiding in maintaining a streamlined and organized media collection.
Example of near duplicate