Fridge

Name

Fridge Objects Dataset

Description

Fridge Objects is a toy dataset which consists of 134 images with 4 classes of beverage container {can, carton, milk bottle, water bottle} pictures taken on different backgrounds.

Annotations Examples

Usage

Example showing how to use this dataset

How to load this dataset

# Imports
from icevision.all import *
import icedata

# Load the Fridge Objects dataset
path = icedata.fridge.load_data()

How to parse this dataset

# Get the class_map, a utility that maps from number IDs to classs names
class_map = icedata.fridge.class_map()

# Randomly split our data into train/valid
data_splitter = RandomSplitter([0.8, 0.2])

# Fridge parser: provided out-of-the-box
parser = icedata.fridge.parser(data_dir=path, class_map=class_map)
train_records, valid_records = parser.parse(data_splitter)

# shows images with corresponding labels and boxes
show_records(train_records[:6], ncols=3, class_map=class_map, show=True)

How to load the pretrained weights of this dataset

class_map = icedata.fridge.class_map()
model = icedata.fridge.trained_models.faster_rcnn_resnet50_fpn()

Dataset folders

Annotations sample

<annotation>
    <folder>images</folder>
    <filename>2.jpg</filename>
    <path>../images/2.jpg</path>
    <source>
        <database>Unknown</database>
    </source>
    <size>
        <width>499</width>
        <height>666</height>
        <depth>3</depth>
    </size>
    <segmented>0</segmented>
    <object>
        <name>milk_bottle</name>
        <pose>Unspecified</pose>
        <truncated>0</truncated>
        <difficult>0</difficult>
        <bndbox>
            <xmin>247</xmin>
            <ymin>192</ymin>
            <xmax>355</xmax>
            <ymax>493</ymax>
        </bndbox>
    </object>
</annotation>

License

Unknown

Relevant Publications

Unknown