6. Data Acquisition
o Download the
FLOWER17 dataset
from here:
http://www.robots.ox.ac.
uk/~vgg/data/flowers/17/
o Unzip the file and you
will see all the 1360
images listed in one
single folder
named *.jpg.
o The FLOWERS17
dataset has 680
images of 17 flower
species classes with
40 images per class.
6
o To build our
training dataset, we
need to create a
master folder
named dataset,
and create Train
and Test folder
inside it.
o Inside train folder,
create 17 folders
corresponding to
the flower species
labels.
11. Configuration
File
◦ This is the configuration file or
the settings file we will be
using to provide inputs to our
system.
◦ This is just a .json file which is a
key-value pair file format to
store data effectively.
11
12. 12
1. Model:
The model key
takes the
parameters –
’mobilenet’.
2. Weights:
The weights key takes the
value ’imagenet’ as we are
using weights from
imagenet. You can also set
this to ’None’.
3. Include-top:
This key takes the
value false specifying that we
are going to take the
features from any
intermediate layer of the
network.
4. Test_size:
The test_size key takes the
value in the range (0.10 - 0.90).
This is to make a split between
your overall data into training
and testing.
5. Seed:
The seed key takes any
value to reproduce same
results everytime you run
the code.
6. Num_classes:
The num_classes specifies the
number of classes or labels
considered for the image
classification problem.
