From 8d825584e6b71179813a880bb97018474d7bc781 Mon Sep 17 00:00:00 2001 From: LufsX Date: Mon, 7 Oct 2024 02:27:11 +0800 Subject: [PATCH] chore: adjust data format --- function.py | 36 ++++++++++++++++++++++++++++++++++-- 1 file changed, 34 insertions(+), 2 deletions(-) diff --git a/function.py b/function.py index 5b6bc50..4911639 100644 --- a/function.py +++ b/function.py @@ -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,