🏷️Finding People & Objects

EyePop.ai has predefined logic to help you find people and objects in common settings. Take a look at the below list to get started.

Interested in running or training your own custom model please contact us. help@eyepop.ai


People Category

Person

Basic model for individual person detection. Works great for finding 1-5 people in a variety of scenes.

Output:

Person w/ 2D Body Points

Detects a person and identifies key 2D body points for posture and movement analysis.

Output:

Person w/ Demographic Data (Age, Gender, Expression)

Enhances person detection with demographic insights, including age, gender, and facial expressions.

Output:

Person w/ 2D Body Points + Demographic Data

Combines 2D body point detection with demographic data for a comprehensive analysis of individuals.

Output:

Person w/ 3D Face, Body & Hands

Advanced model capturing detailed 3D mapping of a person's face, body, and hand movements.

Output:


Common Objects Category

Person + Common Objects

Identifies a person in the context of surrounding common objects, enhancing interaction analysis.

Output:


Expert Detection Category

People + Animals

Detects both people and animals, useful for scenarios involving human-animal interactions.

Output: Bounding Boxes, Trace ID

Output:

People + Devices

Focuses on the interaction between people and various electronic devices.

Output: Bounding Boxes, Trace ID

Person + Sports Equipment

Specialized in identifying sports-related activities and equipment handled by individuals.

Output: Bounding Boxes, Trace ID

Person + Vehicles

Designed for scenarios where individuals interact with various types of vehicles.

Output: Bounding Boxes, Trace ID


Labels

The following labels are recognized by the EyePop.ai Computer Vision API and provided as prediction results. All models include the label for detecting people under the label of person.

People Labels

person

People & Common Objects Labels

eyepop logo, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, cat, dog, horse, umbrella, handbag, suitcase, sports ball, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, bowl, hot dog, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, keyboard, cell phone, microwave, sink, refrigerator, book, clockEPDevice, laptop, mouse, remote, keyboard, cell phone, clock, scissors, hair drier, toothbrush

Expression Labels

Happy, Neutral, Sad, Surprise, Angry, Fear, Disgust

Animal Labels

bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe

Sport Labels

frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket

Vehicle Labels

bicycle, car, motorcycle, bus, train, truck

Age Labels

0-2, 3-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60+

Gender Labels

Male, Female

Device Labels

laptop, mouse, remote, keyboard, cell phone, clock, scissors, hair drier, toothbrush

2D Body Parts Labels

left eye, left ear, left shoulder, left hip, left elbow, left wrist, left knee, left ankle, right eye, right ear, right shoulder, right hip, right elbow, right wrist, right knee, right ankle, nose, midpoint_lowest, midpoint_highest

3D Body Parts Labels

mouth (right), mouth (left), right ear, right eye (outer), right eye, right eye (inner), nose, left eye (inner), left eye, left eye (outer), left ear, right shoulder, left shoulder, left hip, right hip, right elbow, right wrist, right thumb, right pinky, right index, left elbow, left wrist, left thumb, left pinky, left index, right knee, right ankle, right foot index, right heel, left knee, left ankle, left foot index, left heel

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