The most thorough and powerful eye detection is back and better than ever with a massive v2 update. By prior request and to fulfill multiple needs better, the model has been retrained twice, in both paired eyes and single eyes for any use cases, with a much bigger data set.

Dataset: ~7600 custom annotated images.
Training: ~440 Epochs per model, with 60 total runs to tune hyperparameters.
Sleep lost: A bunch.

🖌️ The rules for detecting eyes are carefully honed to select for things people would want to in-paint or highlight, to attempt to avoid false positives:

Match:

☑️ Pairs or individual eyes on any face like structure

☑️ Beady black eyes like animal eyes

☑️ No eyes, but bright highlights in a space where eyes would be e.g. under a hood

☑️ Side-facing eyes if sclera is visible

☑️ (For paired) Single eyes if only one is visible

Ignore:

❌ Goggles, sunglasses, or any types of visor

❌ Skull-like eye sockets or holes, absence of eyes

❌ Flat black eyes with no highlights

About: Eyeful is a custom trained YOLOv8 model meant to be used with ADetailer or any other bbox/detection compatible plugin for Automatic1111 or ComfyUI. This network can also be run completely standalone with Ultralytics.

Detection: This model has a robust custom training dataset, and a custom training pipeline that means it can detect eyes that are in various styles such as painting, artistic, 3d, realistic, anime, manga, even some pixel art.

Settings

Detection Confidence Threshold: >0.40
Model Location (A1111): Extract zip into models/adetailer folder
Model Location (Comfy): Extract zip into models/ultralytics/bbox folder

Failure Cases: There are reasonable limits where an eye may be too stylized or abstract to be highlighted without introducing too many false positives in the training, so this model tries to straddle the line of what you likely would consider an eye worth highlighting, human-like animal eyes: yes, sunglasses: no, etc.

Extreme closeup images will trigger multi-detections if the whole frame is eyeball, but at that point you shouldn't be using this model anyway.