A Yolov8 detection model that detects comic book speech bubbles and sound effects in images.The model can be used as an <a target="_blank" rel="ugc" href="https://github.com/Bing-su/adetailer">ADetailer</a> model (for <a target="_blank" rel="ugc" href="https://github.com/AUTOMATIC1111/">Automatic1111</a> / Stable Diffusion use), or using other <a target="_blank" rel="ugc" href="https://github.com/MNeMoNiCuZ/yolov8-scripts">inference scripts</a> to return detection bounding boxes of watermarks.A small tutorial on how to use the model can be found on this Github: <a target="_blank" rel="ugc" href="https://github.com/MNeMoNiCuZ/yolov8-scripts">https://github.com/MNeMoNiCuZ/yolov8-scripts</a> or this <a target="_blank" rel="ugc" href="https://civarchive.com/articles/4080/training-a-custom-adetailer-model-with-yolov8-detection-model">CivitAI article</a>.<hr />This model is only meant for research purposes. The model is entirely trained on the following dataset: <a target="_blank" rel="ugc" href="https://universe.roboflow.com/yolomanga/speechballoon_comic">yolomanga/speechballoon_comic</a> However, since the dataset is created entirely out of Marvel comic book panels, I think the original author cannot licence the images as CC4. I do not think this model can ba used commercially either.<hr />comic_speechbubble_m_yolov8_v1: <a target="_blank" rel="ugc" href="https://cdn-uploads.huggingface.co/production/uploads/644ed23467c9458c913059ff/hjm3kn-G7mvqUp0RJ2ak5.jpeg"><img src="https://cdn-uploads.huggingface.co/production/uploads/644ed23467c9458c913059ff/hjm3kn-G7mvqUp0RJ2ak5.jpeg" alt="image/jpeg" /></a>comic_speechbubble_s_yolov8_v1<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/2163233d-b346-466d-afc3-8fa65c18a6be/width=525/2163233d-b346-466d-afc3-8fa65c18a6be.jpeg" />Note:The large preview images may not be from the correct model.The A1111 screenshots are from the correct version however.The medium model performs slightly better in general.

Comic Speech Bubble Detection - ADetailer - (comic_speechbubble_m_yolov8)

comicSpeechBubbleDetection_mediumV10.zip

Medium v1.0

Small v1.0

A Yolov8 detection model that detects comic book speech bubbles and sound effects in images.The model can be used as an <a target="_blank" rel="ugc" href="https://github.com/Bing-su/adetailer">ADetailer</a> model (for <a target="_blank" rel="ugc" href="https://github.com/AUTOMATIC1111/">Automatic1111</a> / Stable Diffusion use), or using other <a target="_blank" rel="ugc" href="https://github.com/MNeMoNiCuZ/yolov8-scripts">inference scripts</a> to return detection bounding boxes of watermarks.A small tutorial on how to use the model can be found on this Github: <a target="_blank" rel="ugc" href="https://github.com/MNeMoNiCuZ/yolov8-scripts">https://github.com/MNeMoNiCuZ/yolov8-scripts</a> or this <a target="_blank" rel="ugc" href="https://civitai.com/articles/4080/training-a-custom-adetailer-model-with-yolov8-detection-model">CivitAI article</a>.<hr />This model is only meant for research purposes. The model is entirely trained on the following dataset: <a target="_blank" rel="ugc" href="https://universe.roboflow.com/yolomanga/speechballoon_comic">yolomanga/speechballoon_comic</a> However, since the dataset is created entirely out of Marvel comic book panels, I think the original author cannot licence the images as CC4. I do not think this model can ba used commercially either.<hr />comic_speechbubble_m_yolov8_v1: <a target="_blank" rel="ugc" href="https://cdn-uploads.huggingface.co/production/uploads/644ed23467c9458c913059ff/hjm3kn-G7mvqUp0RJ2ak5.jpeg"><img src="https://cdn-uploads.huggingface.co/production/uploads/644ed23467c9458c913059ff/hjm3kn-G7mvqUp0RJ2ak5.jpeg" alt="image/jpeg" /></a>comic_speechbubble_s_yolov8_v1<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/2163233d-b346-466d-afc3-8fa65c18a6be/width=525/2163233d-b346-466d-afc3-8fa65c18a6be.jpeg" />Note:The large preview images may not be from the correct model.The A1111 screenshots are from the correct version however.The medium model performs slightly better in general.

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