How To Load Images And Text Labels For Cnn Regression From Different Folders

I have two folders, X_train and Y_train. X_train is images, Y_train is vector and .txt files. I try to train CNN for regression. I could not figure out how to take data and train t

Solution 1:

Makes sure x_files and y_files are sorted together, then you can use something like this:

import tensorflow as tf
from glob2 import glob
import os

x_files = glob('X_train\\*.jpg')
y_files = glob('Y_rain\\*.txt')

target_names = ['cat', 'dog']

files = tf.data.Dataset.from_tensor_slices((x_files, y_files))

imsize = 128defget_label(file_path):
    label = tf.io.read_file(file_path)
    return tf.cast(label == target_names, tf.int32)

defdecode_img(img):
    img = tf.image.decode_jpeg(img, channels=3)
    img = tf.image.convert_image_dtype(img, tf.float32)
    img = tf.image.resize(images=img, size=(imsize, imsize))
    return img

defprocess_path(file_path):
    label = get_label(file_path)
    img = tf.io.read_file(file_path)
    img = decode_img(img)
    return img, label

train_ds = files.map(process_path).batch(32)

Then, train_ds can be passed to model.fit() and will return batches of 32 pairs of images, labels.