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Added cache_dir argument for downloading model to a specific directory #20

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Added cache_dir argument for downloading model to a specific directory #20

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15 changes: 9 additions & 6 deletions models/imagebind_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -487,7 +487,7 @@ def forward(self, inputs):
return outputs


def imagebind_huge(pretrained=False):
def imagebind_huge(pretrained=False, cache_dir=None):
model = ImageBindModel(
vision_embed_dim=1280,
vision_num_blocks=32,
Expand All @@ -501,17 +501,20 @@ def imagebind_huge(pretrained=False):
)

if pretrained:
if not os.path.exists(".checkpoints/imagebind_huge.pth"):
cache_dir = cache_dir if cache_dir is not None else ".checkpoints"
ckpt_path = "{}/imagebind_huge.pth".format(cache_dir)

if not os.path.exists(ckpt_path):
print(
"Downloading imagebind weights to .checkpoints/imagebind_huge.pth ..."
"Downloading imagebind weights to {} ...".format(ckpt_path)
)
os.makedirs(".checkpoints", exist_ok=True)
os.makedirs(cache_dir, exist_ok=True)
torch.hub.download_url_to_file(
"https://dl.fbaipublicfiles.com/imagebind/imagebind_huge.pth",
".checkpoints/imagebind_huge.pth",
ckpt_path,
progress=True,
)

model.load_state_dict(torch.load(".checkpoints/imagebind_huge.pth"))
model.load_state_dict(torch.load(ckpt_path))

return model