Label text in images using selected model and threshold
ALA
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Text Detection is an advanced image captioning tool designed to label text within images. Using sophisticated AI models, it identifies and highlights text elements in visual content, enabling applications such as scene understanding, data extraction, and content moderation. With customizable settings like model selection and confidence thresholds, Text Detection offers precise text recognition in various image formats.
• Text Labeling: Automatically detects and labels text in images with high accuracy.
• Multiple Models: Supports a variety of AI models to suit different use cases and performance requirements.
• Threshold Adjustment: Allows users to set confidence thresholds for text detection to filter results.
• ImageFormat Support: Works with popular image formats, including JPEG, PNG, and BMP.
• Real-Time Processing: Enables quick detection and labeling of text for immediate results.
• Accuracy Optimization: Continuously improves text detection accuracy with advanced algorithms.
What models are available for Text Detection?
Text Detection supports multiple state-of-the-art models, including EAST, Tesseract, and CRNN, each optimized for different text detection scenarios.
How do I adjust the confidence threshold?
The confidence threshold can be adjusted using a slider or input field in the tool. A higher threshold increases the confidence level for detections, potentially reducing false positives.
Can Text Detection work with low-quality images?
While Text Detection performs best with clear, high-quality images, it can still process low-quality images, though accuracy may vary depending on the chosen model and image conditions.