imgutils.detect.nudenet

Overview:

This module provides functionality for detecting nudity in images using the NudeNet model.

The module includes functions for preprocessing images, running the NudeNet YOLO model, applying non-maximum suppression (NMS), and postprocessing the results. It utilizes ONNX models hosted on deepghs/nudenet_onnx for efficient inference. The original project is notAI-tech/NudeNet.

Overview of NudeNet Detect (NSFW Warning!!!)

The main function detect_with_nudenet() can be used to perform nudity detection on given images, returning a list of bounding boxes, labels, and confidence scores.

This is an overall benchmark of all the nudenet models:

Note

Here is a detailed list of labels from the NudeNet detection model and their respective meanings:

Label	Description
FEMALE_GENITALIA_COVERED	Detects covered female genitalia in the image.
FACE_FEMALE	Detects the face of a female in the image.
BUTTOCKS_EXPOSED	Detects exposed buttocks in the image.
FEMALE_BREAST_EXPOSED	Detects exposed female breasts in the image.
FEMALE_GENITALIA_EXPOSED	Detects exposed female genitalia in the image.
MALE_BREAST_EXPOSED	Detects exposed male breasts in the image.
ANUS_EXPOSED	Detects exposed anus in the image.
FEET_EXPOSED	Detects exposed feet in the image.
BELLY_COVERED	Detects a covered belly in the image.
FEET_COVERED	Detects covered feet in the image.
ARMPITS_COVERED	Detects covered armpits in the image.
ARMPITS_EXPOSED	Detects exposed armpits in the image.
FACE_MALE	Detects the face of a male in the image.
BELLY_EXPOSED	Detects an exposed belly in the image.
MALE_GENITALIA_EXPOSED	Detects exposed male genitalia in the image.
ANUS_COVERED	Detects a covered anus in the image.
FEMALE_BREAST_COVERED	Detects covered female breasts in the image.
BUTTOCKS_COVERED	Detects covered buttocks in the image.

Note

This module requires onnxruntime version 1.18 or higher.

detect_with_nudenet

imgutils.detect.nudenet.detect_with_nudenet(image: str | PathLike | bytes | bytearray | BinaryIO | Image, topk: int = 100, iou_threshold: float = 0.45, score_threshold: float = 0.25) → List[Tuple[Tuple[int, int, int, int], str, float]]

Detect nudity in the given image using the NudeNet model.

Parameters:

• image – The input image to analyze.

• topk – The maximum number of detections to keep (default: 100).

• iou_threshold – The IoU threshold for NMS (default: 0.45).

• score_threshold – The score threshold for detections (default: 0.25).

Returns:

A list of tuples, each containing:

• A bounding box as (x1, y1, x2, y2)

• A label string

• A confidence score