The People Counting API returns data on the number of detected individuals in an image, along with additional information such as gender and age range for each person detected.

Key fields in the response include "detected_faces," which contains an array of detected individuals, and within each entry, fields like "BoundingBox," "Gender," and "Age-Range" provide detailed information about each person.

The response data is structured as a JSON object. It includes a main array for detected faces, each containing bounding box coordinates, gender probability, and age range, allowing for easy parsing and analysis.

The API primarily accepts an image file as input. Users can customize their requests by adjusting the image quality or format to optimize detection accuracy.

Data accuracy is maintained through advanced image processing algorithms that utilize machine learning techniques to detect and count individuals, ensuring reliable results across various scenarios.

Typical use cases include monitoring crowd sizes at events, analyzing foot traffic in retail environments, and ensuring safety in public spaces by tracking occupancy levels.

Users can leverage the returned data to make informed decisions, such as optimizing store layouts based on foot traffic patterns or ensuring compliance with safety regulations during events.

If partial or empty results are returned, users should check the image quality and ensure that the image is clear and well-lit, as these factors can significantly impact detection accuracy.

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