v0.8.17dev0

March 22, 2023

• More weights pushed to HF hub along with multi-weight support, including: regnet.py, rexnet.py, byobnet.py, resnetv2.py, swin_transformer.py, swin_transformer_v2.py, swin_transformer_v2_cr.py
• Swin Transformer models support feature extraction (NCHW feat maps for swinv2_cr_*, and NHWC for all others) and spatial embedding outputs.
• FocalNet (from https://github.com/microsoft/FocalNet) models and weights added with significant refactoring, feature extraction, no fixed resolution / sizing constraint
• RegNet weights increased with HF hub push, SWAG, SEER, and torchvision v2 weights. SEER is pretty poor wrt to performance for model size, but possibly useful.
• More ImageNet-12k pretrained and 1k fine-tuned timm weights:
  • rexnetr_200.sw_in12k_ft_in1k - 82.6 @ 224, 83.2 @ 288
  • rexnetr_300.sw_in12k_ft_in1k - 84.0 @ 224, 84.5 @ 288
  • regnety_120.sw_in12k_ft_in1k - 85.0 @ 224, 85.4 @ 288
  • regnety_160.lion_in12k_ft_in1k - 85.6 @ 224, 86.0 @ 288
  • regnety_160.sw_in12k_ft_in1k - 85.6 @ 224, 86.0 @ 288 (compare to SWAG PT + 1k FT this is same BUT much lower res, blows SEER FT away)
• Model name deprecation + remapping functionality added (a milestone for bringing 0.8.x out of pre-release). Mappings being added...
• Minor bug fixes and improvements.

Feb 26, 2023

• Add ConvNeXt-XXLarge CLIP pretrained image tower weights for fine-tune & features (fine-tuning TBD) -- see model card
• Update convnext_xxlarge default LayerNorm eps to 1e-5 (for CLIP weights, improved stability)
• 0.8.15dev0