What is the Deep Collector?

The Deep Collector is an AI-powered tool designed to automate the collection, preparation, and labeling of training data for AI models. Instead of manually collecting and preparing data, the Deep Collector uses advanced algorithms to streamline the process, cutting the time and effort required by up to 98%. This makes it one of the fastest and most efficient tools for creating training custom datasets for the Deep Model Customizer, particularly for face recognition and speaker identification.

The Deep Collector incorporates three modules:

• Face dataset creation
  Automatically generate entire datasets using facial images and text information (e.g., from lower thirds), eliminating the need for manual labor.
• Face evaluation
  Analyze entire datasets and receive feedback on your training data quality to enhance face recognition accuracy and eliminating faults.
• Speaker dataset creation
  Automatically generate comprehensive datasets by utilizing audio recordings from speakers and accompanying text information, such as transcripts or belly bands.
  
  

• Use Cases:
• Face Recognition Datasets: Automatically extract and label faces from media archives, enabling the training of custom facial recognition models.
• Speaker Identification: Build a comprehensive speaker dataset by using audio recordings and linking them with metadata such as transcripts.