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Roll20 commited on
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718e2e4
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1 Parent(s): 5df2a5d

app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -134,7 +134,7 @@ def score(input_img):
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'swin_large_patch4_window7_224', out_features = 1, inp_channels = 3, pretrained=False)
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- model.load_state_dict(torch.load('swin_large_patch4_window7_224_fold0_half.pth'))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [1])
@@ -147,7 +147,7 @@ def score(input_img):
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'beit_large_patch16_224', out_features = 1, inp_channels = 3, pretrained=False)
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- model.load_state_dict(torch.load('beit_large_patch16_224_fold0_half.pth'))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [0])
@@ -159,7 +159,7 @@ def score(input_img):
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'swin_large_patch4_window12_384_in22k', out_features = 1, inp_channels = 3, pretrained=False)
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- model.load_state_dict(torch.load('swin_large_patch4_window12_384_in22k_fold0_half.pth'))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, 384, [0])
@@ -186,7 +186,7 @@ def score(input_img):
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  modelfiles = glob(Config.model_base_dir + Config_exp77.model_dir + Config.model_file_ext)
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  test_preds_fold = []
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  model = PetNet_exp77(model_name = 'beit_large_patch16_224', out_features = 1, inp_channels = 3, pretrained=False)
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- model.load_state_dict(torch.load('beit_large_patch16_224_fold1_half.pth'))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [0])
 
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'swin_large_patch4_window7_224', out_features = 1, inp_channels = 3, pretrained=False)
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+ model.load_state_dict(torch.load('swin_large_patch4_window7_224_fold0_half.pth', map_location=torch.device('cpu')))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [1])
 
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'beit_large_patch16_224', out_features = 1, inp_channels = 3, pretrained=False)
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+ model.load_state_dict(torch.load('beit_large_patch16_224_fold0_half.pth', map_location=torch.device('cpu')))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [0])
 
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  test_preds_model = []
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  test_preds_fold = []
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  model = PetNet(model_name = 'swin_large_patch4_window12_384_in22k', out_features = 1, inp_channels = 3, pretrained=False)
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+ model.load_state_dict(torch.load('swin_large_patch4_window12_384_in22k_fold0_half.pth', map_location=torch.device('cpu')))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, 384, [0])
 
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  modelfiles = glob(Config.model_base_dir + Config_exp77.model_dir + Config.model_file_ext)
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  test_preds_fold = []
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  model = PetNet_exp77(model_name = 'beit_large_patch16_224', out_features = 1, inp_channels = 3, pretrained=False)
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+ model.load_state_dict(torch.load('beit_large_patch16_224_fold1_half.pth', map_location=torch.device('cpu')))
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  model = model.float()
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  model.eval()
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  test_preds_fold = tta_fn(thefile, model, Config.im_size, [0])