Can we Ignore unnecessary classes in the Tensorflow object detection API by only omitting labels in pbtxt label map file? - tensorflow

Question

So I am trying to create custom datasets for object detection using the Tensorflow Object detection API. When working with open source datasets the annotation files I have come across as PASCAL VOC xmls or jsons. These contain a list of labels for each class for example:
<annotation>
<folder>open_images_volume</folder>
<filename>0d2471ff2d033ccd.jpg</filename>
<path>/mnt/open_images_volume/0d2471ff2d033ccd.jpg</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>1024</width>
<height>1024</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>Chair</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>8</xmin>
<ymin>670</ymin>
<xmax>409</xmax>
<ymax>1020</ymax>
</bndbox>
</object>
<object>
<name>Table</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>232</xmin>
<ymin>654</ymin>
<xmax>555</xmax>
<ymax>1020</ymax>
</bndbox>
</object>
</annotation>
Here the annotation file describes 2 classes, Table & chair. I am only interested in detecting chairs, which is why the pbtxt file I have generated is simply
item {
id: 1
display_name: "Chair"
}
My question is that will the model train on simply the annotations of the class "Chair" because that's what I have defined via the label_map.pbtxt or do I need to manually scrape all the annotation files and remove the bounding box co-ordinates through regex or xmltree in order to make sure the additional bounding boxes do not interfere with training. So is it possible to select only custom classes for training even if the annotation files have additional classes through the TF API or is it necessary to clean up the entire datasets and manually remove unnecessary class labels? Will it affect training in any way?

Answer 1

You can use a .pbtxt that only has the classes that you need to train and you don't have to change the xmls.
Also, make sure to change the num_classes: your_num_classes.