import json
import os
import numpy as np

from PIL import Image
from tqdm import tqdm
from glob import glob

from .dataset import Dataset
from .video import Video


class UVADTVideo(Video):
    """
    Args:
        name: video name
        root: dataset root
        video_dir: video directory
        init_rect: init rectangle
        img_names: image names
        gt_rect: groundtruth rectangle
        attr: attribute of video
    """
    def __init__(self, name, root, video_dir, init_rect, img_names,
            gt_rect, attr, load_img=False):
        super(UVADTVideo, self).__init__(name, root, video_dir,
                init_rect, img_names, gt_rect, attr, load_img)

def ca():
        
    
    path='./VisDrone2018-SOT-test'
    
    name_list=os.listdir(path+'/sequences')
    name_list.sort()
    
    b=[]
    for i in range(len(name_list)):
        b.append(name_list[i])
    c=[]
    
    for jj in range(len(name_list)):
        imgs=path+'/sequences/'+str(name_list[jj])
        txt=path+'/annotations/'+str(name_list[jj])+'.txt'
        bbox=[]
        f = open(txt)               # 返回一个文件对象
        file= f.readlines()
        li=os.listdir(imgs)
        li.sort()
        for ii in range(len(file)):
            li[ii]='sequences/'+name_list[jj]+'/'+li[ii]
    
            line = file[ii].strip('\n').split(',')
            
            try:
                line[0]=int(line[0])
            except:
                line[0]=float(line[0])
            try:
                line[1]=int(line[1])
            except:
                line[1]=float(line[1])
            try:
                line[2]=int(line[2])
            except:
                line[2]=float(line[2])
            try:
                line[3]=int(line[3])
            except:
                line[3]=float(line[3])
            bbox.append(line)
            
        if len(bbox)!=len(li):
            print (jj)
        f.close()
        c.append({'attr':[],'gt_rect':bbox,'img_names':li,'init_rect':bbox[0],'video_dir':name_list[jj]})
        
    d=dict(zip(b,c))

    return d
class VISDRONEDataset(Dataset):
    """
    Args:
        name: dataset name, should be 'OTB100', 'CVPR13', 'OTB50'
        dataset_root: dataset root
        load_img: wether to load all imgs
    """
    def __init__(self, name, dataset_root, load_img=False):
        super(VISDRONEDataset, self).__init__(name, dataset_root)
        # with open(os.path.join(dataset_root, name+'.json'), 'r') as f:
        #     meta_data = json.load(f)
        meta_data=ca()
        # load videos
        pbar = tqdm(meta_data.keys(), desc='loading '+name, ncols=100)
        self.videos = {}
        for video in pbar:
            pbar.set_postfix_str(video)
            self.videos[video] = UVADTVideo(video,
                                          dataset_root,
                                          meta_data[video]['video_dir'],
                                          meta_data[video]['init_rect'],
                                          meta_data[video]['img_names'],
                                          meta_data[video]['gt_rect'],
                                          meta_data[video]['attr'],
                                          load_img)

        # set attr
        attr = []
        for x in self.videos.values():
            attr += x.attr
        attr = set(attr)
        self.attr = {}
        self.attr['ALL'] = list(self.videos.keys())
        for x in attr:
            self.attr[x] = []
        for k, v in self.videos.items():
            for attr_ in v.attr:
                self.attr[attr_].append(k)
