This is the pretrained weights and some other detector weights of ControlNet.
Modellquelle
Quellenbeschreibung
This is the pretrained weights and some other detector weights of ControlNet.
See also: https://github.com/lllyasviel/ControlNet
ControlNet/models/control_sd15_canny.pth
ControlNet/models/control_sd15_depth.pth
Quellen
1 QuelleVerifiziert 30. Aug.
Modellartefakte
15 Artefakteannotator/ckpts/body_pose_model.pth
pth · 200 MB · SHA-256 25a948c16078…b746 · Hugging Face
Herunterladenannotator/ckpts/dpt_hybrid-midas-501f0c75.pt
pt · 470 MB · SHA-256 501f0c75b3bc…0853 · Hugging Face
HerunterladenQuellenauszüge
2 AuszügeControlNet/models/control_sd15_hed.pth
ControlNet/models/control_sd15_mlsd.pth
ControlNet/models/control_sd15_normal.pth
ControlNet/models/control_sd15_openpose.pth
ControlNet/models/control_sd15_scribble.pth
ControlNet/models/control_sd15_seg.pth
ControlNet/annotator/ckpts/body_pose_model.pth
ControlNet/annotator/ckpts/hand_pose_model.pth
ControlNet/annotator/ckpts/dpt_hybrid-midas-501f0c75.pt
ControlNet/annotator/ckpts/mlsd_large_512_fp32.pth
ControlNet/annotator/ckpts/mlsd_tiny_512_fp32.pth
ControlNet/annotator/ckpts/network-bsds500.pth
ControlNet/annotator/ckpts/upernet_global_small.pth
ControlNet/training/fill50k.zip
Special Thank to the great project - Mikubill' A1111 Webui Plugin !
We also thank Hysts for making Gradio demo in Hugging Face Space as well as more than 65 models in that amazing Colab list!
Thank haofanwang for making ControlNet-for-Diffusers!
We also thank all authors for making Controlnet DEMOs, including but not limited to fffiloni, other-model, ThereforeGames, RamAnanth1, etc!
The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
annotator/ckpts/hand_pose_model.pth
pth · 141 MB · SHA-256 b76b00d17509…c600 · Hugging Face
annotator/ckpts/mlsd_large_512_fp32.pth
pth · 6,05 MB · SHA-256 5696f168eb2c…a082 · Hugging Face
Herunterladenannotator/ckpts/mlsd_tiny_512_fp32.pth
pth · 2,49 MB · SHA-256 3f2323cfb9fa…0b94 · Hugging Face
Herunterladenannotator/ckpts/network-bsds500.pth
pth · 56,1 MB · SHA-256 58a858782f5f…1a94 · Hugging Face
Herunterladenannotator/ckpts/upernet_global_small.pth
pth · 197 MB · SHA-256 bebfa1264c10…d970 · Hugging Face
Herunterladenmodels/control_sd15_openpose.pth
pth · 5,32 GB · SHA-256 d19ffffeeaff…f591 · Hugging Face
Herunterladenmodels/control_sd15_scribble.pth
pth · 5,32 GB · SHA-256 591bc5a70a16…9ad3 · Hugging Face
Herunterladen--- license: openrail --- This is the pretrained weights and some other detector weights of ControlNet. See also: https://github.com/lllyasviel/ControlNet # Description of Files ControlNet/models/control_sd15_canny.pth - The ControlNet+SD1.5 model to control SD using canny edge detection. ControlNet/models/control_sd15_depth.pth - The ControlNet+SD1.5 model to control SD using Midas depth estimation. ControlNet/models/control_sd15_hed.pth - The ControlNet+SD1.5 model to control SD using HED edge detection (soft edge). ControlNet/models/control_sd15_mlsd.pth - The ControlNet+SD1.5 model to control SD using M-LSD line detection (will also work with traditional Hough transform). ControlNet/models/control_sd15_normal.pth - The ControlNet+SD1.5 model to control SD using normal map. Best to use the normal map generated by that Gradio app. Other normal maps may also work as long as the direction is correct (left looks red, right looks blue, up looks green, down looks purple). ControlNet/models/control_sd15_openpose.pth - The ControlNet+SD1.5 model to control SD using OpenPose pose detection. Directly manipulating pose skeleton should also work. ControlNet/models/control_sd15_scribble.pth - The ControlNet+SD1.5 model to control SD using human scribbles. The model is trained with boundary edges with very strong data augmentation to simulate boundary lines similar to that drawn by human. ControlNet/models/control_sd15_seg.pth - The ControlNet+SD1.5 model to control SD using semantic segmentation. The protocol is ADE20k. ControlNet/annotator/ckpts/body_pose_model.pth - Third-party model: Openpose’s pose detection model. ControlNet/annotator/ckpts/hand_pose_model.pth - Third-party model: Openpose’s hand detection model. ControlNet/annotator/ckpts/dpt_hybrid-midas-501f0c75.pt - Third-party model: Midas depth estimation model. ControlNet/annotator/ckpts/mlsd_large_512_fp32.pth - Third-party model: M-LSD detection model. ControlNet/annotator/ckpts/mlsd_tiny_512_fp32.pth - Third-party model: M-LSD’s another smaller detection model (we do not use this one). ControlNet/annotator/ckpts/network-bsds500.pth - Third-party model: HED boundary detection. ControlNet/annotator/ckpts/upernet_global_small.pth - Third-party model: Uniformer semantic segmentation. ControlNet/training/fill50k.zip - The data for our training tutorial. # Related Resour...
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