import os, sys
import csv

try:
    import numpy as np
except:
    # print "Failed to import numpy package."
    sys.exit(-1)
try:
    import imageio
except:
    print("Please install the module 'imageio' for image processing, e.g.")
    print("pip install imageio")
    sys.exit(-1)


# print an error message and quit
def print_error(message, user_fault=False):
    sys.stderr.write('ERROR: ' + str(message) + '\n')
    if user_fault:
        sys.exit(2)
    sys.exit(-1)


# if string s represents an int
def represents_int(s):
    try:
        int(s)
        return True
    except ValueError:
        return False


def read_label_mapping(filename, label_from='raw_category', label_to='nyu40id'):
    assert os.path.isfile(filename)
    mapping = dict()
    with open(filename) as csvfile:
        reader = csv.DictReader(csvfile, delimiter='\t')
        for row in reader:
            mapping[row[label_from]] = int(row[label_to])
    # if ints convert 
    if represents_int(list(mapping.keys())[0]):
        mapping = {int(k): v for k, v in mapping.items()}
    return mapping


# input: scene_types.txt or scene_types_all.txt
def read_scene_types_mapping(filename, remove_spaces=True):
    assert os.path.isfile(filename)
    mapping = dict()
    lines = open(filename).read().splitlines()
    lines = [line.split('\t') for line in lines]
    if remove_spaces:
        mapping = {x[1].strip(): int(x[0]) for x in lines}
    else:
        mapping = {x[1]: int(x[0]) for x in lines}
    return mapping


# color by label
def visualize_label_image(filename, image):
    height = image.shape[0]
    width = image.shape[1]
    vis_image = np.zeros([height, width, 3], dtype=np.uint8)
    color_palette = create_color_palette()
    for idx, color in enumerate(color_palette):
        vis_image[image == idx] = color
    imageio.imwrite(filename, vis_image)


# color by different instances (mod length of color palette)
def visualize_instance_image(filename, image):
    height = image.shape[0]
    width = image.shape[1]
    vis_image = np.zeros([height, width, 3], dtype=np.uint8)
    color_palette = create_color_palette()
    instances = np.unique(image)
    for idx, inst in enumerate(instances):
        vis_image[image == inst] = color_palette[inst % len(color_palette)]
    imageio.imwrite(filename, vis_image)


# color palette for nyu40 labels
def create_color_palette():
    return [
        (0, 0, 0),
        (174, 199, 232),  # wall
        (152, 223, 138),  # floor
        (31, 119, 180),  # cabinet
        (255, 187, 120),  # bed
        (188, 189, 34),  # chair
        (140, 86, 75),  # sofa
        (255, 152, 150),  # table
        (214, 39, 40),  # door
        (197, 176, 213),  # window
        (148, 103, 189),  # bookshelf
        (196, 156, 148),  # picture
        (23, 190, 207),  # counter
        (178, 76, 76),
        (247, 182, 210),  # desk
        (66, 188, 102),
        (219, 219, 141),  # curtain
        (140, 57, 197),
        (202, 185, 52),
        (51, 176, 203),
        (200, 54, 131),
        (92, 193, 61),
        (78, 71, 183),
        (172, 114, 82),
        (255, 127, 14),  # refrigerator
        (91, 163, 138),
        (153, 98, 156),
        (140, 153, 101),
        (158, 218, 229),  # shower curtain
        (100, 125, 154),
        (178, 127, 135),
        (120, 185, 128),
        (146, 111, 194),
        (44, 160, 44),  # toilet
        (112, 128, 144),  # sink
        (96, 207, 209),
        (227, 119, 194),  # bathtub
        (213, 92, 176),
        (94, 106, 211),
        (82, 84, 163),  # otherfurn
        (100, 85, 144)
    ]