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chore: adjust data format
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LufsX
2024-10-07 02:27:11 +08:00
parent eb5af644a2
commit 8d825584e6
1 changed files with 34 additions and 2 deletions
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function.py
+34 -2
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@@ -85,10 +85,42 @@ def img_to_vector(filename):
if __name__ == "__main__":
# 以下代码可用于测试，可自行随意修改
train_data, train_labels = load_dataset("trainingDigits")
test_data = "0000000000000011000000000000000000000000000011111000000000000000000000000000111111000000000000000000000000111111111000000000000000000000001111111110000000000000000000000011111111000000000000000000000001111111100000000000000000000000111111111000000000000000000000001111111100000000000000000000000011111111000000000000000000000000111111110000000000000000000000001111111100000000000000000000000011111110000000000000000000000001111111100000000000000000000000011111111000000000000000000000000111111110000000000000000000000001111111111111000000000000000000011111111111111110000000000000000111111111111111110000000000000011111111111111111110000000000000111111111111111111100000000000000111111111111111111000000000000001111111111111111110000000000000001111111111001111111000000000000011111111100011111110000000000000011111111001111111100000000000000111111111111111110000000000000000111111111111111100000000000000000111111111111111000000000000000000111111111111000000000000000000000111111111000000000000000000000000000111100000000000"
test_data = (
"00000000000000110000000000000000"
"00000000000011111000000000000000"
"00000000000011111100000000000000"
"00000000001111111110000000000000"
"00000000001111111110000000000000"
"00000000001111111100000000000000"
"00000000011111111000000000000000"
"00000000111111111000000000000000"
"00000000111111110000000000000000"
"00000000111111110000000000000000"
"00000000111111110000000000000000"
"00000000111111110000000000000000"
"00000000111111100000000000000000"
"00000001111111100000000000000000"
"00000001111111100000000000000000"
"00000001111111100000000000000000"
"00000001111111111111000000000000"
"00000001111111111111111000000000"
"00000001111111111111111100000000"
"00000011111111111111111110000000"
"00000011111111111111111110000000"
"00000001111111111111111110000000"
"00000001111111111111111110000000"
"00000000111111111100111111100000"
"00000000111111111000111111100000"
"00000000011111111001111111100000"
"00000000011111111111111111000000"
"00000000001111111111111111000000"
"00000000000111111111111111000000"
"00000000000011111111111100000000"
"00000000000001111111110000000000"
"00000000000000000111100000000000"
)
predicted_label = classify(
np.array([int(char) for char in test_data]).reshape(1, 1024),
train_data,