import json

import cv2
import numpy as np
import pickle as pickle

import LFUtilities
import WebAppSettings as settings
#from ORBRescorer import ORBRescorer
from BEBLIDRescorer import BEBLIDRescorer
#from LATCHRescorer import LATCHRescorer
from GEMSearcher import GEMSearcher
import GEMExtractor as fe
import ORBExtractor as orb_lf
import BEBLIDExtractor as beblid_lf
import LATCHExtractor as latch_lf


class Searcher:

    GEM_THRESHOLD = 0.3

    def __init__(self):
        # self.dataset = h5py.File(settings.dataset_file, 'r')['rmac'][...]

        # np.save('/media/Data/data/beni_culturali/deploy/dataset', self.dataset)
        self.ids = np.loadtxt(settings.DATASET_IDS, dtype=str).tolist()

        self.search_engine = GEMSearcher()

       # self.orb_rescorer = ORBRescorer()
        self.beblid_rescorer = BEBLIDRescorer()
        #self.latch_rescorer = LATCHRescorer()

    def get_id(self, idx):
        return self.search_engine.get_id(idx)

    def add(self, img_file, id):
       # self.save(True)

        #desc = fe.extract(img_file)
        #orb = lf.extract(img_file)
        #self.search_engine.add(desc, id)
        #self.rescorer.add(orb)

        #self.save()
        print('added ' + id)

    def remove(self, id):
        #self.save(True)
        #self.search_engine.remove(id)
        #self.rescorer.remove(idx)
        #self.save()
        print('removed ' + id)

    def search_by_id(self, query_id, k=10, rescorer=False, lf_impl='BEBLID'):
        kq = k
        if rescorer:
            kq = settings.k_reorder
        res = self.search_engine.search_by_id(query_id, kq)
        if rescorer:
            if lf_impl == 'BEBLID':
                res_lf = self.beblid_rescorer.rescore_by_id(query_id, res)
            #res = res_lf if res_lf else res[:k]
            res = res_lf
        return res

    def search_by_img(self, query_img, k=10, rescorer=False, lf_impl='BEBLID'):
        if rescorer:
            print(lf_impl)
        kq = k
        if rescorer:
            kq = settings.k_reorder
        query_desc = fe.extract(query_img)
        res = self.search_engine.search_by_img(query_desc, kq)
        print(res[0])
        if rescorer:
            if lf_impl == 'BEBLID':
                query_lf = beblid_lf.extract(query_img)
                res_lf = self.beblid_rescorer.rescore_by_img(query_lf, res)
            if res_lf:
                label = res_lf[0][0].split('/')[0]
                res = [label, res_lf[0][1]]
            else:
                res = None
        else:
            if res[0][1] > self.GEM_THRESHOLD:
                label = res[0][0].split('/')[0]
                res = [label, res[0][1]]
            else:
                res = None

        return res

    def save(self, is_backup=False):
        self.search_engine.save(is_backup)
        #self.rescorer.save(is_backup)