Wsrtjtyk

I have a dataset for the self-driving car. My X values are the names of the images. Example would be

array([['img_2.png'],

       ['img_3.png'],

       ['img_4.png'],

       ...,

       ['img_6405.png'],

       ['img_6406.png'],

       ['img_6407.png']], dtype=object)

I found out that model performs good if we have some kind of batch_generator. I found that template code.

def batch_generator(image_paths, steering_ang, batch_size, istraining):



  while True:

    batch_img = 

    batch_steering = 



    for i in range(batch_size):

      random_index = random.randint(0, len(image_paths) - 1)



      if istraining:

        im = random_augment(image_paths[random_index])

        steering = steering_ang[random_index]

      else:

        im = mpimg.imread(image_paths[random_index])

        steering = steering_ang[random_index]



      im = img_preprocess(im)

      batch_img.append(im)

      batch_steering.append(steering)

    yield (np.asarray(batch_img), np.asarray(batch_steering))  

I changed this function to for my use but when i apply it.

x_train_gen, y_train_gen = next(batch_generator(X_train, y_train, 1, 1))

x_valid_gen, y_valid_gen = next(batch_generator(X_valid, y_valid, 1, 0))

I get the following error TypeError: Object does not appear to be a 8-bit string path or a Python file-like object. I understand the error, image is not an array but a string. How can i convert string of the image path to the array

I don't know what you're doing in the img_preprocess() function but from what I see there are 2 possible problems:

1. You have to append the path to the image to the image name: path_to_image = path_to_image_dir + '/' + image




2. You have to actually open the image to get it's array. You can use Pillow or OpenCV:
   PIL.Image.open(path_to_image) or cv2.imread(path_to_image)