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Run experiments: gp instance recognition
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woodRock committed Sep 10, 2024
1 parent 1dedee4 commit b0f7069
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10 changes: 5 additions & 5 deletions code/gp/results.py
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Expand Up @@ -36,7 +36,7 @@
test_accs = []

# Skip the print tree statements.
skip = {'species': 2, 'part': 6, 'oil': 7, 'oil_simple': 2, 'cross-species': 3}
skip = {'species': 2, 'part': 6, 'oil': 7, 'oil_simple': 2, 'cross-species': 3, 'instance-recognition': 0}
if dataset not in skip.keys():
raise ValueError(f"Invalid dataset specified: {dataset} not in {skip.keys()}")
skip_amount = skip[dataset]
Expand All @@ -54,11 +54,11 @@
content = f.readlines()
# Extract the train, validation and test accuracy.
# The training accuracy is on the 10th to last line.
train_acc: float = float(content[-8 - skip_amount].split(sep=' ')[2])
train_acc: float = float(content[-6 - skip_amount].split(sep=' ')[2])
# The validation accuracy is on the 9th to last line.
val_acc: float = float(content[-7 - skip_amount].split(sep=' ')[2])
val_acc: float = float(content[-5 - skip_amount].split(sep=' ')[2])
# The test accuracy is on the 8th to last line.
test_acc: float = float(content[-6 - skip_amount].split(sep=' ')[2])
test_acc: float = float(content[-4 - skip_amount].split(sep=' ')[2])
# Append the accuracy to an array.
train_accs.append(train_acc)
val_accs.append(val_acc)
Expand All @@ -80,4 +80,4 @@
mean, std = torch.mean(val_accs), torch.std(val_accs)
print(f"Validation: mean: {mean} +\- {std}")
mean, std = torch.mean(test_accs), torch.std(test_accs)
print(f"Test: mean: {mean} +\- {std}")
print(f"Test: mean: {mean} +\- {std}")

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