Pinned

1. Data_Acquisition Data_Acquisition

   1

   path = '/kaggle/input/insulation-joint-training-set-prorail/trainset_insulation_joint/labels.csv'

   2

   df = pd.read_csv(path, sep=';')

   3

   print(df)

   4

   5

   # This part is just to join the filepath of images  with the name of images 

2. Data_understanding Data_understanding

   1

   #Put all the images into a list

   2

   listOfImageNames = []

   3

   for dirname, _, filenames in os.walk('/kaggle/input/insulation-joint-training-set-prorail/trainset_insulation_joint/images/'):

   4

       for filename in filenames:

   5

           #print(os.path.join(dirname, filename))

3. Load the restnet50 model Load the restnet50 model

   1

   Input_shape = (224,224,3)

   2

   resnet50_model = keras.applications.ResNet50(include_top=False, weights="imagenet", input_shape=Input_shape)

   3

   #resnet50_model.summary()

   4

   #, pooling='max'

   5

   #, pooling='avg'