imgutils.detect.booru_yolo

Overview:

This module provides functionality for object detection using the Booru YOLO model.

The Booru YOLO model is sourced from aperveyev/booru_yolo and model files are hosted on deepghs/booru_yolo.

Overview of Booru YOLO Detect (NSFW Warning!!!)

This is an overall benchmark of all the booru yolo models:

Here is the explanations of each label:

Model Labels and Descriptions

No.	Label	Description
0	head	Anime pretty girl and not only
1	bust	Torso part from collarbone center to pair of covered breasts
2	boob	Bust with no bra, nipples mostly visible, generally NSFW
3	shld	Shoulder and maybe one breast viewed mostly in profile, exactly rear view excluded
4	sideb	Uncovered version of shld, with nipples or other NSFW visual marks
5	belly	From belly button to hips half (stocking line), knees below belly, mostly covered
6	nopan	No panty-like clothes on bikini area (regardless of censoring), evidently NSFW belly
7	butt	Buttock area visible at least partially from behind, more or less covered, standing or sitting
8	ass	Uncovered NSFW version of butt
9	split	Sitting with legs open wide (90+ degrees), typically with at least one knee above belly
10	sprd	Strongly NSFW version of split
11	vsplt	Stand split or visually similar pose
12	vsprd	Strongly NSFW version of vsplit
13	hip	Full or almost full hip(-s) side view with knee(-s) above belly, usually when sitting or lying
14	wing	Mostly dragon or pony related
15	feral	All-four non-human torso
16	hdrago	Dragon style head
17	hpony	Pony style head
18	hfox	Cartoon fox / dog head - Zootopia Nick Wilde
19	hrabb	Cartoon rabbit head - Zootopia Judy Hopps or bunnygirl
20	hcat	Cartoon cat or anime catgirl head (less sharp muzzle compared to hfox)
21	hbear	Cartoon bear head
22	jacko	Memetic “Jack’O contest pose” with a head toward viewer
23	jackx	Jacko viewed from behind, sometimes strongly NSFW
24	hhorse	Horse head first implemented in aa09
25	hbird	Bird head first implemented in aa09

Here are the list of available models.

Available Models (PP Series)

Model Name	Release Time	Description
yolov8s_pp09	2023.11	PP model focusing on NSFW content with 9 specialized classes, providing advanced detection capabilities for specific NSFW scenarios.
yolov8s_pp12	2024.2	Final patch for PP models, continuing the focus on specialized NSFW content detection with enhanced capabilities and improvements from previous versions.
yolov8m_pp13	2024.2	PP model final patch, focusing on specific NSFW content with 9 specialized classes, offering advanced NSFW detection capabilities.

Available Models (AS Series)

Model Name	Release Time	Description
yolov8n_as01	2023.12	Spinoff model with 26 classes trained for 80 epochs on an SFW subset. This model was eventually abandoned due to ineffective results.
yolov8m_as02	2023.12	Spinoff model started using an SFW training subset. It includes 26 classes and was trained for 30 epochs, offering a more public-friendly model with reduced NSFW content.
yolov8m_as03	2024.1	Advanced spinoff model from as02 with 26 classes, trained for 60 epochs. This SFW subset model aims to reduce bottlenecks and improve reproducibility of results.

Available Models (AA Series)

Model Name	Release Time	Description
yolov8s_aa06	2023.8	Initial version for current reincarnation with 24 classes trained for 90 epochs. Focuses on general torso components and includes some NSFW content.
yolov8s_aa09	2023.10	Added HHORSE and HBIRD classes, updating the dataset with more head closeups and adjusting for large hats, trained from aa06.
yolov8s_aa10	2023.12	Major training dataset update from aa09, focusing on improving detection of HHORSE and HBIRD and fixing issues with heads wearing large hats.
yolov8s_aa11	2024.1	Latest mainstream general torso components model with 26 classes. It includes an update from aa10 with outstanding mAP scores, though noted to be not completely fair due to training set biases.

detect_with_booru_yolo

imgutils.detect.booru_yolo.detect_with_booru_yolo(image: str | PathLike | bytes | bytearray | BinaryIO | Image, model_name: str = 'yolov8s_aa11', conf_threshold: float = 0.25, iou_threshold: float = 0.7, **kwargs) → List[Tuple[Tuple[int, int, int, int], str, float]]

Perform object detection on an image using the Booru YOLO model.

Parameters:

• image (ImageTyping) – Input image to perform detection on.

• model_name (str, optional) – Name of the Booru YOLO model to use, defaults to ‘yolov8s_aa11’.

• conf_threshold (float, optional) – Confidence threshold for detection, defaults to 0.25.

• iou_threshold (float, optional) – IOU threshold for non-maximum suppression, defaults to 0.7.

Returns:

List of detected objects, each represented as (bounding_box as (x1, y1, x2, y2), label, confidence).

Return type:

List[Tuple[Tuple[int, int, int, int], str, float]]

Example:

>>> from imgutils.detect import detect_with_booru_yolo
...
>>> detections = detect_with_booru_yolo("path/to/image.jpg")
>>> for box, label, confidence in detections:
...     print(f"Detected {label} with confidence {confidence:.2f} at {box}")