import numpy as np
import json
import os
from pycocotools import mask as maskUtils
from PIL import Image
from tqdm import tqdm
from pycocotools.coco import COCO
import random
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_pascal_part(base_image_dir):
    coco_api_pascal_part = COCO(
        os.path.join(base_image_dir, "vlpart", "pascal_part", "train.json")
    )
    all_classes = coco_api_pascal_part.loadCats(coco_api_pascal_part.getCatIds())
    class_map_pascal_part = {}
    for cat in all_classes:
        cat_main, cat_part = cat["name"].strip().split(":")
        name = (cat_main, cat_part)
        class_map_pascal_part[cat["id"]] = name
    img_ids = coco_api_pascal_part.getImgIds()
    print("pascal_part: ", len(img_ids))
    return class_map_pascal_part, img_ids, coco_api_pascal_part


base_image_dir = '/mnt/workspace/workgroup/yuanyq/code/LISA/dataset'
class_map, img_ids, coco_api = init_pascal_part(base_image_dir)
final_data = []
for idx in tqdm(range(len(img_ids))):
    dic = {}
    
    img_id = img_ids[idx]
    image_info = coco_api.loadImgs([img_id])[0]
    file_name = image_info["file_name"]
    file_name = os.path.join(
        "VOCdevkit", "VOC2010", "JPEGImages", file_name
    )

    annIds = coco_api.getAnnIds(imgIds=image_info["id"])
    anns = coco_api.loadAnns(annIds)
    cats = []
    
    for ann in anns:
        sampled_cls = class_map[ann["category_id"]]
        if isinstance(sampled_cls, tuple):
            obj, part = sampled_cls
            if random.random() < 0.5:
                name = obj + " " + part
            else:
                name = "the {} of the {}".format(part, obj)
        else:
            name = sampled_cls
        cats.append(name)
    masks = []  
    for ann in anns:
        masks.append(singleMask2rle(coco_api.annToMask(ann)))

    dic['image'] = 'vlpart/pascal_part/'+file_name
    dic['cat'] = cats
    dic['masks'] = masks
    final_data.append(dic)
    
    
print(len(final_data))
with open('pascal_part.json', 'w') as f:
    f.write(json.dumps(final_data))