Error creating unique object detection data set <ValueError:tuple.index(x):x not intuple>

Asked 1 months ago, Updated 1 months ago, 6 views

I have already posted it on teratail.
https://teratail.com/questions/225527

When creating an object detection program, you try to look inside your own data set
(first_datum=train_dataset[0])
ERROR. Is the data set strange because the program on the reference site worked?It can be thought thatI don't know at all, so please let me.Thank you for your cooperation.

import chainer
import cupy
import chain cv
import matplotlib
importos
import xml.etree.ElementTree as ET

import numpy as np

from chainercv.datasets import VOCBboxDataset


bccd_labels=('ROCK', 'MOUNTAIN')# Changes


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, different
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]

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

!pip install chainercv#Installing ChainerCV

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

importos
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, different

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]


<announcement>
    <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>
        <diffault>0</diffault>
        <bndbox>
            <xmin>242.6123427801162</xmin>
            <ymin>279.4234910191407</ymin>
            <xmax>720</xmax>
            <ymax>706.8194993286604</ymax>
        </bndbox>
    </object>
</annotation>

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

/usr/local/lib/python 3.6/dist-packages/chain/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/python 3.6/dist-packages/chainercv/chainer_experimental/datasets/slicable/slicable_dataset.py inget_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/python 3.6/dist-packages/chainercv/chainer_experimental/datasets/slicable/getter_dataset.py inget_example_by_keys(self,index,key_indices)
     87_,getter_index,key_index=self._keys [key_index]
     88 if getter_index not in cache:
--- >89cache [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 intuple

chainer

2022-09-30 11:22

1 Answers

The first line of the error code reads "ValueErrorTraceback (most recent call last)", so look at the last line.

Then it says "ValueError:tuple.index(x):x not intuple" and the code above it is
"--- 35 label.append(bccd_labels.index(name)))" indicates where the error occurred.

If you associate the code "label.append(bccd_labels.index(name)))" in this line with the error "tuple.index(x):x not intuple",
 The reason for the error is that the variable bccd_labels table did not contain the contents of the variable name.

If you go back to how the values of each variable have changed since the error occurred, you may be able to get to the cause of the problem.

Try your best.


2022-09-30 11:22

If you have any answers or tips


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