Update README.md

README.md

@@ -38,6 +38,15 @@ conda install pytorch torchvision cudatoolkit=9.0 -c pytorch
 python setup.py develop
 ```
 
+Download OSNet models.
+
+```python
+from huggingface_hub import snapshot_download
+
+# This will download the entire repo (containing all models) to cache_dir
+snapshot_download(repo_id="kaiyangzhou/osnet", cache_dir="./")
+```
+
 Use Torchreid as a feature extractor in your project.
 
 ```python
@@ -45,7 +54,7 @@ from torchreid.utils import FeatureExtractor
 
 extractor = FeatureExtractor(
     model_name='osnet_x1_0',
-    model_path='a/b/c/model.pth.tar',
+    model_path='a/b/c/model.pth',
     device='cuda'
 )
 
@@ -59,4 +68,20 @@ image_list = [
 
 features = extractor(image_list)
 print(features.shape) # output (5, 512)
-```
+```
+
+# Model list
+
+Models pre-trained on ImageNet are named in the following format: `osnet_x<scale>_imagenet.pth`.
+
+Available re-id models:
+- osnet_ain_x1_0_msmt17_256x128_amsgrad_ep50_lr0.0015_coslr_b64_fb10_softmax_labsmth_flip_jitter.pth
+- osnet_ibn_x1_0_msmt17_combineall_256x128_amsgrad_ep150_stp60_lr0.0015_b64_fb10_softmax_labelsmooth_flip_jitter.pth
+- osnet_x1_0_msmt17_combineall_256x128_amsgrad_ep150_stp60_lr0.0015_b64_fb10_softmax_labelsmooth_flip_jitter.pth
+- osnet_x0_75_msmt17_combineall_256x128_amsgrad_ep150_stp60_lr0.0015_b64_fb10_softmax_labelsmooth_flip_jitter.pth
+- osnet_x0_5_msmt17_combineall_256x128_amsgrad_ep150_stp60_lr0.0015_b64_fb10_softmax_labelsmooth_flip_jitter.pth
+- osnet_x0_25_msmt17_combineall_256x128_amsgrad_ep150_stp60_lr0.0015_b64_fb10_softmax_labelsmooth_flip_jitter.pth
+
+`ain` and `ibn` models are more generalizable. Please refer to https://arxiv.org/abs/1910.06827.
+
+`osnet_x1_0`, `osnet_x0_75`, `osnet_x0_5`, and `osnet_x0_25` are OSNet models of different sizes. Please refer to https://arxiv.org/abs/1905.00953.