質問編集履歴
5
エラーメッセージの変更
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```
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C:\pleiades\python\3\lib\site-packages\numpy\core\_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
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return array(a, dtype, copy=False, order=order)
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Exception in Tkinter callback
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Traceback (most recent call last):
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File "C:\pleiades\python\3\lib\tkinter\__init__.py", line 1705, in __call__
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return self.func(*args)
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File "C:\pleiades\workspace\LogicCulc\LogicCulc_Chainer_v2\NetworkCreator\NetworkCreator.py", line 485, in selected_ds
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newtrain_data = np.asarray(train_data)
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File "C:\pleiades\python\3\lib\site-packages\numpy\core\_asarray.py", line 83, in asarray
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return array(a, dtype, copy=False, order=order)
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ValueError: could not broadcast input array from shape (3,150,150) into shape (3)
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4
補足情報を追加した
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### 補足情報（FW/ツールのバージョンなど）
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chainerのデータセットの作り方は以下のサイトを参考にしました
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https://qiita.com/tommyfms2/items/c3fa0cb258c17468cb30
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タイトル変更
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リストからnumpy配列に変換できない
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コードを全文入れた
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### 前提・実現したいこと
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現在自作のデータセットを作り、そこからchainerを使って学習しようとしています。
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現在自作のカラー画像データセットを作り、そこからchainerを使って学習しようとしています。
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画像データセットは以下のように作っています
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```ここに言語名を入力
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import os
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import numpy as np
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import glob
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import cv2
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import chainer
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import pickle
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from chainer import cuda, Function, gradient_check, report, training, utils, Variable
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from chainer import datasets, iterators, optimizers, serializers
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from chainer.datasets import tuple_dataset, TupleDataset
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image_dir0 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\buildings"
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image_dir1 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\forest"
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image_dir2 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\glacier"
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image_dir3 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\mountain"
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image_dir4 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\sea"
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image_dir5 = r"C:\Users\user\Desktop\archive\seg_train\seg_train\street"
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image_dir6 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\buildings"
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image_dir7 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\forest"
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image_dir8 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\glacier"
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image_dir9 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\mountain"
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image_dir10 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\sea"
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image_dir11 = r"C:\Users\user\Desktop\archive\seg_test\seg_test\street"
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search_pattern = '*.jpg'
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datas0 = []
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datas1 = []
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datas2 = []
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datas3 = []
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datas4 = []
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datas5 = []
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datas6 = []
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datas7 = []
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datas8 = []
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datas9 = []
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datas10= []
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datas11= []
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#(画像データセットの作り方(これを12個作ります。))
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for image_path in glob.glob(os.path.join(image_dir0,search_pattern)):
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1
タイトルを変更いたしました
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chainerを用いた自作画像セット作成
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