from google.colab import drive
drive.mount('/content/drive')

!pip install aicrowd-cli
%load_ext aicrowd.magic

%aicrowd login

!rm -rf data
!mkdir data
%aicrowd ds dl -c age-prediction -o data

!unzip -qq data/train.zip -d data/train
!unzip -qq data/val.zip -d data/val
!unzip -qq data/test.zip -d data/test

!pip install facenet_pytorch

import pandas as pd
import numpy as np
import torch
import csv
import os
import cv2
import glob
import torch
from torch import nn
import numpy as np
from matplotlib import pyplot as plt
from tqdm import tqdm
import albumentations as albu
from facenet_pytorch import InceptionResnetV1, MTCNN

def open_img(name):
    img = cv2.imread(name)
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    return img

def show(img):
    plt.xticks([]), plt.yticks([])
    plt.imshow(img)


def show_all(images, cols=3):
    num_rows = (len(images) - 1) // cols + 1
    plt.rcParams['figure.figsize'] = [20, 7 * num_rows]
    for i, im in enumerate(images):
        plt.subplot(num_rows, cols, i+1)
        show(im)
    plt.show()
    plt.rcParams['figure.figsize'] = [20, 10]


device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

names = ["0000v", "00boq", "01bn8", "03p0f", "04gd1", "04tx0"]
# names = ["dloyr", "e6yjc", "k675i", "ni3p4", "ro01p", "svx4s"]
imgs = [open_img("data/val/"+name+".jpg") for name in names]

show_all(imgs)