import os

import numpy as np
from PIL import Image
from tqdm import tqdm

from deeplab import Deeplab

class miou_Deeplab(Deeplab):
    def detect_image(self, image):
        orininal_h = np.array(image).shape[0]
        orininal_w = np.array(image).shape[1]

        img, nw, nh = self.letterbox_image(image,(self.model_image_size[1],self.model_image_size[0]))
        img = [np.array(img)/127.5-1]
        img = np.asarray(img)
        
        pr = self.model.predict(img)[0]
        pr = pr.argmax(axis=-1).reshape([self.model_image_size[0],self.model_image_size[1]])
        pr = pr[int((self.model_image_size[0]-nh)//2):int((self.model_image_size[0]-nh)//2+nh), int((self.model_image_size[1]-nw)//2):int((self.model_image_size[1]-nw)//2+nw)]
        
        image = Image.fromarray(np.uint8(pr)).resize((orininal_w,orininal_h), Image.NEAREST)
        return image

deeplab = miou_Deeplab()

image_ids = open("VOCdevkit/VOC2007/ImageSets/Segmentation/val.txt",'r').read().splitlines()

if not os.path.exists("./miou_pr_dir"):
    os.makedirs("./miou_pr_dir")

for image_id in tqdm(image_ids):
    image_path = "./VOCdevkit/VOC2007/JPEGImages/"+image_id+".jpg"
    image = Image.open(image_path)
    image = deeplab.detect_image(image)
    image.save("./miou_pr_dir/" + image_id + ".png")