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def get_cropped_image(image_file_name, df_row):
    """Returns a cropped image."""
    image = cv2.imread(image_file_name)
    x = df_row["bbox_x_top_left"]
    y = df_row["bbox_y_top_left"]
    width = df_row["bbox_x_bot_right"] - x + 1
    height = df_row["bbox_y_bot_right"] - y + 1
    cropped_image = image[y:y+height, x:x+width]
    return cropped_image


num_images = 100
num_rows, num_cols = 10, 10
input_dir = "faces/"
output_dir = "cropped_faces/"
extension = ".jpg"
bbox_cols = [
    "bbox_x_top_left",
    "bbox_y_top_left",
    "bbox_x_bot_right",
    "bbox_y_bot_right",
]

f, axarr = plt.subplots(num_rows, num_cols, figsize=(20, 20))
curr_row = 0
for i in range(num_images):
    # Get image info
    df_row = df.iloc[i]
    image_id = df_row["id"]
    # Get cropped image    
    image_file_name = f"{input_dir}{image_id}{extension}"
    cropped_image = get_cropped_image(image_file_name, df_row)
    # find the column by taking the current index modulo 3
    col = i % num_rows
    # plot on relevant subplot    
    axarr[col, curr_row].imshow(cv2.cvtColor(cropped_image, cv2.COLOR_BGR2RGB))
    axarr[col, curr_row].axis('off')
    if col == num_cols - 1:
        # we have finished the current row, so increment row counter
        curr_row += 1

plt.savefig(f"{output_dir}face_thumbnails.jpg")