import numpy as np
import json
import os
from pycocotools import mask as maskUtils
from PIL import Image
from tqdm import tqdm
def singleMask2rle(mask):
    rle = maskUtils.encode(np.array(mask[:, :, None], order='F', dtype="uint8"))[0]
    rle["counts"] = rle["counts"].decode("utf-8")
    return rle

def init_ade20k(base_image_dir):
    with open("../ade20k_classes.json", "r") as f:
        ade20k_classes = json.load(f)
    ade20k_classes = np.array(ade20k_classes)
    image_ids = sorted(
        os.listdir(os.path.join(base_image_dir, "ade20k/images", "training"))
    )
    ade20k_image_ids = []
    for x in image_ids:
        if x.endswith(".jpg"):
            ade20k_image_ids.append(x[:-4])
    ade20k_images = []
    for image_id in ade20k_image_ids:  # self.descriptions:
        ade20k_images.append(
            os.path.join(
                base_image_dir,
                "ade20k",
                "images",
                "training",
                "{}.jpg".format(image_id),
            )
        )
    ade20k_labels = [
        x.replace(".jpg", ".png").replace("images", "annotations")
        for x in ade20k_images
    ]
    print("ade20k: ", len(ade20k_images))
    return ade20k_classes, ade20k_images, ade20k_labels

base_image_dir = '/mnt/workspace/workgroup/yuanyq/code/LISA/dataset'
classes, images, labels = init_ade20k(base_image_dir)
final_data = []
for idx in tqdm(range(len(images))):
    dic = {}
    image_path = images[idx]
    label_path = labels[idx]
    label = Image.open(label_path)
    label = np.array(label)
   
    label[label == 0] = 255
    label -= 1
    label[label == 254] = 255
    
    unique_label = np.unique(label).tolist()
    if 255 in unique_label:
        unique_label.remove(255)
    if len(unique_label) == 0:
        continue
    
    cats = []
    for class_id in unique_label:
        cats.append(classes[class_id])
    masks = []
    for class_id in unique_label:
        msk = label==class_id
        rle = singleMask2rle(msk)
        masks.append(rle)
    
    dic['image'] = image_path.replace('/mnt/workspace/workgroup/yuanyq/code/LISA/dataset/', '')
    dic['cat'] = cats
    dic['masks'] = masks
    final_data.append(dic)
    
print(len(final_data))
with open('ade20k.json', 'w') as f:
    f.write(json.dumps(final_data))