Update README.md

README.md

@@ -1,3 +1,46 @@
----
-license: mit
----
+---
+license: mit
+library_name: torchgeo
+---
+
+Model rehosted from https://github.com/wangzhecheng/SkyScript
+
+Original source: https://opendatasharing.s3.us-west-2.amazonaws.com/SkyScript/ckpt/SkyCLIP_ViT_L14_top30pct.zip
+
+Model weights extracted below:
+
+```python
+import os
+import torch
+import hashlib
+
+import timm
+from open_clip.factory import create_model_and_transforms
+from timm.models.vision_transformer import _convert_openai_clip
+
+
+path = "SkyCLIP_ViT_L14_top30pct/epoch_20.pt"
+encoder = "ViT-L-14"
+model, _, preprocess_val = create_model_and_transforms(encoder, path, weights_only=False)
+print(preprocess_val)
+model_timm = timm.create_model("vit_large_patch14_clip_224", pretrained=False, num_classes=768)
+converted = _convert_openai_clip(model.state_dict(), model_timm)
+model_timm.load_state_dict(converted, strict=True)
+
+filename = "vit_large_patch14_224_skyclip_30pct.pth"
+torch.save(model_timm.state_dict(), filename)
+md5 = hashlib.md5(open(filename, "rb").read()).hexdigest()[:8]
+os.rename(filename, filename.replace(".pth", f"-{md5}.pth"))
+```
+
+The preprocessing transforms are:
+
+```
+Compose(
+    Resize(size=224, interpolation=bicubic, max_size=None, antialias=True)
+    CenterCrop(size=(224, 224))
+    <function _convert_to_rgb at 0x33047ff60>
+    ToTensor()
+    Normalize(mean=(0.48145466, 0.4578275, 0.40821073), std=(0.26862954, 0.26130258, 0.27577711))
+)
+```