teratailにても投稿済です
https://teratail.com/questions/225527

概要

物体検出プログラム作成時、独自データセットの中を見ようとして
（first_datum = train_dataset[0]）
エラー。参考サイトのプログラムでは動作したため、データセットの中身がおかしい？とかんがえられます。まったくわからないため教えていただきたいです。よろしくお願いします。

エラーの出たプログラム

import chainer
import cupy
import chainercv
import matplotlib
import os
import xml.etree.ElementTree as ET

import numpy as np

from chainercv.datasets import VOCBboxDataset


bccd_labels = ('ROCK', 'MOUNTAIN')#変更箇所


class BCCDDataset(VOCBboxDataset):

    def _get_annotations(self, i):
        id_ = self.ids[i]
        anno = ET.parse(
            os.path.join(self.data_dir, 'Annotations', id_ + '.xml'))

        bbox = []
        label = []
        difficult = []
        for obj in anno.findall('object'):
            bndbox_anno = obj.find('bndbox')

            bbox.append([
                int(bndbox_anno.find(tag).text) - 1
                for tag in ('ymin', 'xmin', 'ymax', 'xmax')])
            name = obj.find('name').text.lower().strip()
            label.append(bccd_labels.index(name))
            print(bccd_labels.index(obj.find('name').text.lower().strip()))
        bbox = np.stack(bbox).astype(np.float32)
        label = np.stack(label).astype(np.int32)

        difficult = np.array(difficult, dtype=np.bool)
        return bbox, label, difficult
train_dataset = BCCDDataset('rock_detect_dataset/BCCD', 'train')
valid_dataset = BCCDDataset('rock_detect_dataset/BCCD', 'val')
test_dataset = BCCDDataset('rock_detect_dataset/BCCD', 'test')
print('Number of images in "train" dataset:', len(train_dataset))
print('Number of images in "valid" dataset:', len(valid_dataset))
print('Number of images in "test" dataset:', len(test_dataset))
first_datum = train_dataset[0]

参考サイト・コード

https://japan-medical-ai.github.io/medical-ai-course-materials/notebooks/06_Blood_Cell_Detection.html

!pip install chainercv  # ChainerCVのインストール

import chainer
import cupy
import chainercv
import matplotlib
!if [ ! -d BCCD_Dataset ]; then git clone https://github.com/Shenggan/BCCD_Dataset.git; fi

import os
import xml.etree.ElementTree as ET

import numpy as np

from chainercv.datasets import VOCBboxDataset


bccd_labels = ('rbc', 'wbc', 'platelets')


class BCCDDataset(VOCBboxDataset):

    def _get_annotations(self, i):
        id_ = self.ids[i]

        anno = ET.parse(
            os.path.join(self.data_dir, 'Annotations', id_ + '.xml'))

        bbox = []
        label = []
        difficult = []
        for obj in anno.findall('object'):
            bndbox_anno = obj.find('bndbox')

            bbox.append([
                int(bndbox_anno.find(tag).text) - 1
                for tag in ('ymin', 'xmin', 'ymax', 'xmax')])
            name = obj.find('name').text.lower().strip()
            label.append(bccd_labels.index(name))
        bbox = np.stack(bbox).astype(np.float32)
        label = np.stack(label).astype(np.int32)

        difficult = np.array(difficult, dtype=np.bool)
        return bbox, label, difficult

train_dataset = BCCDDataset('BCCD_Dataset/BCCD', 'train')
valid_dataset = BCCDDataset('BCCD_Dataset/BCCD', 'val')
test_dataset = BCCDDataset('BCCD_Dataset/BCCD', 'test')

first_datum = train_dataset[0]

xml例

<annotation>
    <folder>JPGImages</folder>
    <filename>hogehoge.jpg</filename>
    <path>hogehoge</path>
    <source>
        <database>Unknown</database>
    </source>
    <size>
        <width>720</width>
        <height>1080</height>
        <depth>3</depth>
    </size>
    <segmented>0</segmented>
    <object>
        <name>MOUNTAIN</name>
        <pose>Unspecified</pose>
        <truncated>0</truncated>
        <difficult>0</difficult>
        <bndbox>
            <xmin>242.6123427801162</xmin>
            <ymin>279.4234910191407</ymin>
            <xmax>720</xmax>
            <ymax>706.8194993286604</ymax>
        </bndbox>
    </object>
</annotation>

エラーコード

ValueErrorTraceback (most recent call last)
<ipython-input-59-8cd07929f6af> in <module>
----> 1 first_datum = train_dataset[0]
      2 print(first_datum[0].shape, first_datum[0].dtype)

/usr/local/lib/python3.6/dist-packages/chainer/dataset/dataset_mixin.py in __getitem__(self, index)
     65             return [self.get_example(i) for i in index]
     66         else:
---> 67             return self.get_example(index)
     68 
     69     def __len__(self):

/usr/local/lib/python3.6/dist-packages/chainercv/chainer_experimental/datasets/sliceable/sliceable_dataset.py in get_example(self, index)
     96         if isinstance(self.keys, tuple):
     97             return self.get_example_by_keys(
---> 98                 index, tuple(range(len(self.keys))))
     99         else:
    100             return self.get_example_by_keys(index, (0,))[0]

/usr/local/lib/python3.6/dist-packages/chainercv/chainer_experimental/datasets/sliceable/getter_dataset.py in get_example_by_keys(self, index, key_indices)
     87             _, getter_index, key_index = self._keys[key_index]
     88             if getter_index not in cache:
---> 89                 cache[getter_index] = self._getters[getter_index](index)
     90             if key_index is None:
     91                 example.append(cache[getter_index])

<ipython-input-55-501a46a571b5> in _get_annotations(self, i)
     33                 for tag in ('ymin', 'xmin', 'ymax', 'xmax')])
     34             name = obj.find('name').text.lower().strip()
---> 35             label.append(bccd_labels.index(name))
     36             print(bccd_labels.index(obj.find('name').text.lower().strip()))
     37         bbox = np.stack(bbox).astype(np.float32)

ValueError: tuple.index(x): x not in tuple