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トップに関する質問機械学習で、ファイルを３つ以上読み込むとエラーが起きる

編集履歴

質問編集履歴

1

エラーが出るまでの全てのプログラムを書きました。

2020/07/05 07:03

投稿

nifeP
nifeP

スコア1

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test CHANGED
@@ -2,6 +2,176 @@
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  ```python
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+ !pip install icrawler
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+
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+ ```
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+ ```python
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+ # from icrawler.builtin import GoogleImageCrawler
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+
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+ # もつ煮の画像を100枚取得
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+
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+ # crawler = GoogleImageCrawler(storage={"root_dir": "moosuni"})
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+
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+ # crawler.crawl(keyword="もつ煮", max_num=100)
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+
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+ from icrawler.builtin import BingImageCrawler
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+
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+
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+
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+ # もつ煮の画像を100枚取得
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+ crawler = BingImageCrawler(storage={"root_dir": "motsuni"})
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+ crawler.crawl(keyword="もつ煮", max_num=100)
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+ ```
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+ ```python
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+
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+ # ナポリタンの画像を100枚取得
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+ # crawler = GoogleImageCrawler(storage={"root_dir": "naporitan"})
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+
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+ # crawler.crawl(keyword="ナポリタン", max_num=100)
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+
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+ from icrawler.builtin import BingImageCrawler
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+
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+
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+
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+ # ナポリタンの画像を100枚取得
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+ crawler = BingImageCrawler(storage={"root_dir": "naporitan"})
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+ crawler.crawl(keyword="ナポリタン", max_num=100)
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+ ```
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+ ```python
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+ # ラーメンの画像を100枚取得
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+ # crawler = GoogleImageCrawler(storage={"root_dir": "ra-men"})
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+
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+ # crawler.crawl(keyword="ラーメン", max_num=100)
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+
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+ from icrawler.builtin import BingImageCrawler
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+
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+
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+
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+ # ラーメンの画像を100枚取得
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+ crawler = BingImageCrawler(storage={"root_dir": "ra-men"})
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+ crawler.crawl(keyword="醤油ラーメン", max_num=100)
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+ ```
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+ ```python
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+ from PIL import Image
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+ import os, glob
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+
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+ import numpy as np
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+ from PIL import ImageFile
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+ # IOError: image file is truncated (0 bytes not processed)回避のため
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+ ImageFile.LOAD_TRUNCATED_IMAGES = True
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+
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+ classes = ["motsuni", "naporitan", "ra-men"]
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+
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+ num_classes = len(classes)
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+ image_size = 64
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+ num_testdata = 25
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+
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+ X_train = []
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+ X_test = []
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+ y_train = []
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+ y_test = []
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+ for index, classlabel in enumerate(classes):
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+ photos_dir = "./" + classlabel
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+ files = glob.glob(photos_dir + "/*.jpg")
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+ for i, file in enumerate(files):
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+ image = Image.open(file)
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+ image = image.convert("RGB")
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+ image = image.resize((image_size, image_size))
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+ data = np.asarray(image)
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+ if i < num_testdata:
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+ X_test.append(data)
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+ y_test.append(index)
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+ else:
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+ for angle in range(-20, 20, 5):
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+ img_r = image.rotate(angle)
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+ data = np.asarray(img_r)
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+ X_train.append(data)
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+ y_train.append(index)
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+ img_trains = img_r.transpose(Image.FLIP_LEFT_RIGHT)
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+ data = np.asarray(img_trains)
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+ X_train.append(data)
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+ y_train.append(index)
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+ X_train = np.array(X_train)
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+ X_test = np.array(X_test)
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+ y_train = np.array(y_train)
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+ y_test = np.array(y_test)
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+ xy = (X_train, X_test, y_train, y_test)
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+ np.save("./ryouri.npy", xy)
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+ ```
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+ ```python
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+
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  from keras.models import Sequential
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  from keras.layers import Conv2D, MaxPooling2D
@@ -16,7 +186,7 @@
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- classes = ["motsuni", "naporitan", "jirou"]
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+ classes = ["motsuni", "naporitan", "ra-men"]
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  num_classes = len(classes)
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@@ -206,4 +376,8 @@
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+ 使う画像は、上のコードでウェブから拾ってきています。
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+
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  ３つ以上のファイルを機械学習するためにはどのようにすればいいか、教えていただけると嬉しいです。