This model is designed to detect pairs of eyes, unlike this model <a target="_blank" rel="ugc" href="https://civarchive.com/models/150925/eyes-detection-adetailer">https://civarchive.com/models/150925/eyes-detection-adetailer</a> , mine is designed to detect pairs of eyes. Thanks to the creator, this has inspired me to train this modelThis is my first project on yolov8Recommended confidence threshold 0.3-0.4The model works:1) With anime characters;2) With humans;3) With animals;4) with anyone with pronounced eyes;5) Works at close and very far distances.The model also detects closed eyes or if one eye is open but both eyes are visible.What doesn't work:1) If a character has one eye covered by something (patch, hair, etc), the model does not recognize it;2) If there is only one eye in the image with no context that there is another eye.How to use:How to install:<ol><li>Go to <a target="_blank" rel="ugc" href="https://github.com/Bing-su/adetailer">https://github.com/Bing-su/adetailer</a> and install Adetailer</li><li>Place the this file (<a target="_blank" rel="ugc" href="https://civarchive.com/api/download/models/370554">full_eyes_detect_yolo8s.pt</a>) in "stable-diffusion-webui\models\adetailer"</li><li>and reload WebUI.</li></ol>Install for Automatic1111:<ol><li>Open "Extensions" tab.</li><li>Open "Install from URL" tab in the tab.</li><li>Enter <a target="_blank" rel="ugc" href="https://github.com/Bing-su/adetailer.git">https://github.com/Bing-su/adetailer.git</a> to "URL for extension's git repository".</li><li>Press "Install" button.</li><li>Wait 5 seconds, and you will see the message "Installed into stable-diffusion-webui\extensions\adetailer. Use Installed tab to restart".</li><li>Go to "Installed" tab, click "Check for updates", and then click "Apply and restart UI". (The next time you can also use this method to update extensions.)</li><li>Completely restart A1111 webui including your terminal. (If you do not know what is a "terminal", you can reboot your computer: turn your computer off and turn it on again.)</li></ol>

Files with SHA256: ef852da3c10ba01907189227ef3997bbec157375188b92de43df42142e6172e8