質問編集履歴
4
ライブラリ追加
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@@ -178,4 +178,10 @@
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# print("PREDICT: ", pred)
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return pred
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```
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```
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### ライブラリなど
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184
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windows10
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185
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python3.6
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186
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pyxel
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187
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scikit-learn 0.22
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3
エラーとコードの追加
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@@ -17,13 +17,39 @@
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17
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今回分からないエラーは
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```エラー
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-
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20
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Image has saved correctly.
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21
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C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\utils\deprecation.py:144: FutureWarning: The sklearn.neighbors.classification module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.neighbors. Anything that cannot be imported from sklearn.neighbors is now part of the private API.
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warnings.warn(message, FutureWarning)
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23
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C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\utils\deprecation.py:144: FutureWarning: The sklearn.neighbors.kd_tree module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.neighbors. Anything that cannot be imported from sklearn.neighbors is now part of the private API.
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24
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warnings.warn(message, FutureWarning)
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25
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C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\utils\deprecation.py:144: FutureWarning: The sklearn.neighbors.dist_metrics module is deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.neighbors. Anything that cannot be imported from sklearn.neighbors is now part of the private API.
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warnings.warn(message, FutureWarning)
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27
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C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\base.py:318: UserWarning: Trying to unpickle estimator KNeighborsClassifier from version 0.21.3 when using version 0.22.1. This might lead to breaking code or invalid results. Use at your own risk.
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UserWarning)
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29
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Traceback (most recent call last):
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30
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File "paint.py", line 87, in <module>
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31
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App()
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32
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File "paint.py", line 31, in __init__
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33
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pyxel.run(self.update, self.draw)
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34
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File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\pyxel\app.py", line 255, in run
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35
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main_loop()
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36
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File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\pyxel\app.py", line 247, in main_loop
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self._update_frame()
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File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\pyxel\app.py", line 438, in _update_frame
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39
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self._update()
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File "paint.py", line 57, in update
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self.pred_digit = model.load_predict()
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File "C:\Users\ユーザー名\Desktop\AI\pyxelDigitRecognition\model.py", line 43, in load_predict
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43
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pred = loaded_model.predict(img)[0] # np.array to int
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File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\neighbors\_classification.py", line 173, in predict
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45
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neigh_dist, neigh_ind = self.kneighbors(X)
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46
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File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\neighbors\_base.py", line 580, in kneighbors
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n_samples_fit = self.n_samples_fit_
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AttributeError: 'KNeighborsClassifier' object has no attribute 'n_samples_fit_'
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```
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コード
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```
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```paint.py
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# 3rd party
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import numpy as np
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from PIL import Image
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@@ -104,4 +130,52 @@
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104
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App()
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```
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```model.py
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import numpy as np
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import pickle
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from PIL import Image
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from sklearn.datasets import load_digits
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from sklearn.model_selection import train_test_split
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from sklearn.neighbors import KNeighborsClassifier
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142
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143
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def train():
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144
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"""Train k-nearest neighbors model with Digits dataset
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"""
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digits = load_digits()
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X = digits.data
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y = digits.target
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149
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# print(X.shape) # (1797, 64)
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# print(y.shape) # (1797,)
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X_train,X_test,y_train,y_test = train_test_split(X, y)
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knn = KNeighborsClassifier()
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knn.fit(X_train, y_train)
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# print(knn.score(X_test, y_test)) # 0.98 lol
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# save model
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with open('knn_digit.pkl', 'wb') as f:
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pickle.dump(knn, f)
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162
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164
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def load_predict() -> int:
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"""load a trained model and predict
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"""
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167
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with open('knn_digit.pkl', 'rb') as f:
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loaded_model = pickle.load(f)
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# Open image and extract features
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img = Image.open("images/screen_shot.png")
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img = img.convert('L') # convert (r,g,b) to gray scale (0-255)
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img = (255 - np.array(img))//16 + 1 # convert to 0-15
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img = img.reshape(1, 64)
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pred = loaded_model.predict(img)[0] # np.array to int
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# print("PREDICT: ", pred)
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return pred
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+
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107
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```
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2
エラー
title
CHANGED
|
File without changes
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body
CHANGED
|
@@ -17,6 +17,8 @@
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|
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17
17
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今回分からないエラーは
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18
18
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|
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19
19
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```エラー
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20
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+
File "C:\Users\ユーザー名\AppData\Local\Programs\Python\Python36\lib\site-packages\sklearn\neighbors\_base.py", line 612, in kneighbors
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21
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n_samples_fit = self.n_samples_fit_
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AttributeError: 'KNeighborsClassifier' object has no attribute 'n_samples_fit_'
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```
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22
24
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1
リンク
title
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body
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@@ -7,7 +7,8 @@
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7
7
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4.数字を学習したAIがその画像を認識する
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8
8
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5.結果を出力
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9
9
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10
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+
今回の参考サイトは
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10
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-
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11
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+
[ペイントソフトを作って、ついでに手書き数字認識もする](https://qiita.com/odanny/items/eee3d99522bb01fdd111?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items)
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11
12
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12
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基本的にサイトに書かれていることしかしていないので、以下のエラーが一体何なのかわからず困っています。
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13
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K近傍法とやらのエラーっぽい感じなのはわかるのですが・・・。
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