import requests
import subprocess
from time import sleep
import json
import os
import urllib.request as req
from PIL import Image

import os, sys


instances_url = 'http://localhost:8042/instances/'
series_url = 'http://localhost:8042/series/'
studies_url= 'http://localhost:8042/studies/'
local_path = 'C:\\Users\\emico\\Desktop\\biomedical\\'  #cartella principale dove memorizzare le immagini, file di input e output del parallel indexer e le similar images finali
lireSolr_path = 'C:\\Users\\emico\\Desktop\\LireSolr'   #path del progetto LireSolr dal quale runnare il task ParallelIndexer
solr_path = 'C:\\solr-7.2.1\\bin'   #path di Solr
curl_path = 'C:\\curl-7.59.0-win64-mingw\\bin'  #necessario se Windows non riconosce il comando curl
cmp = "C:\\Users\\emico\\Desktop\\Query_Images\\provapolmone.jpg"       #Inserire qui il percorso della query by example
separator = '\\'

get_images = requests.get(instances_url).json()     #recupera immagini/istanze
patientPhog=[]
patientJcd=[]
studyPhog=[]
studyJcd=[]
seriesPhog=[]
seriesJcd=[]
instancePhog=[]
instanceJcd=[]


def getImagesFromPacs():
    for each in get_images:
        r = requests.get(instances_url+each+'').json()      #get campi per ogni immagine
        #print(r)
        id_image = r["ID"]
        series = r["ParentSeries"]          # uno dei campi è ParentSeries, che contiene la serie di riferimento di quella img
        s = requests.get(series_url+series+'').json()   #get Serie specificata prima
        study = s["ParentStudy"]                    #la serie ha un campo Study che è lo studio cui appartiene
        stud = requests.get(studies_url+study+'').json()        #get Studio
        patient_id = stud["PatientMainDicomTags"]["PatientID"]  #lo studio ha un campo MainDicom Tag con l'id del paziente

        filepath = os.path.join(local_path+patient_id+separator+study+separator+series)

        if not os.path.exists(filepath):        #crea cartella paziente->studio->serie->img con urlretrieve della lib urllib.request
              os.makedirs(filepath)
        req.urlretrieve(instances_url+each+'/preview', filepath+separator+id_image+".jpg")

        #Resize delle immagini per renderle compatibili al ParallelIndexer
        im = Image.open(filepath+separator+id_image+".jpg")
        imResize = im.resize((512, 510), Image.ANTIALIAS)
        imResize.save(filepath+separator+id_image+".jpg",'JPEG', quality=100)

#Creazione file images.txt con i percorsi delle immagini da passare poi al ParallelIndexer
def listImg():
    for root, dirs, files in os.walk(local_path):
        for file in files:
            if file.endswith('.jpg'):
                f= open(local_path+'images.txt', 'a')
                f.write(os.path.join(root, file+"\n"))

#Run del ParallelIndexer
def callParallelIndexer():
    subprocess.call('gradlew runParallelIndexer', cwd=lireSolr_path,shell=True)

def solrConnection():
    subprocess.call('solr start', cwd=solr_path,shell=True)
    #Carica images-out.xml
    subprocess.call('curl http://localhost:8983/solr/lire/update -H "Content-Type: text/xml" --data-binary "<delete><query>*:*</query></delete>"', cwd=curl_path, shell=True)
    subprocess.call('curl http://localhost:8983/solr/lire/update -H "Content-Type: text/xml" --data-binary @'+local_path+'images-out.xml', cwd=curl_path, shell=True)
    subprocess.call('curl http://localhost:8983/solr/lire/update -H "Content-Type: text/xml" --data-binary "<commit/>"', cwd=curl_path, shell=True)

    core = "lire"
    requestHandler = "lireq"
    wt= "json"

    solrconn = requests.get('http://localhost:8983/solr/'+core+'/'+requestHandler+'?cmp='+cmp+'&q=*:*&wt='+wt).json()
    phog = solrconn["RisultatiPhogManhattan"]["docs"]       #Si è scelto di estrarre come features phog e jcd
    jcd= solrconn["RisultatiJcdCosine"]["docs"]

    #Prendo ad esempio i primi 20 risultati rilevanti di phog e di jcd.
    for p in phog[:19]:
        patientPhog.append(p["patient"])
        studyPhog.append(p["study"])
        seriesPhog.append(p["series"])
        instancePhog.append(p["instance"])


    for each in jcd[:19]:
        patientJcd.append(each["patient"])
        studyJcd.append(each["study"])
        seriesJcd.append(each["series"])
        instanceJcd.append(each["instance"])


def getSimilarImagesPacs():

    contjcd=0
    contphog=0

    for each in instanceJcd:
        img = each.split(".")[0]
        pathimgjcd = os.path.join(local_path+"similarImages"+separator+"jcd"+separator+patientJcd[contjcd]+separator+studyJcd[contjcd]+separator+seriesJcd[contjcd])
        if not os.path.exists(pathimgjcd):
            os.makedirs(pathimgjcd)
        req.urlretrieve(instances_url+img+'/preview', pathimgjcd+separator+img+".jpg")
        contjcd = contjcd + 1


    for p in instancePhog:
        imgp = p.split(".")[0]
        pathimgp = os.path.join(local_path+separator+"similarImages"+separator+"phog"+separator+patientPhog[contphog]+separator+studyPhog[contphog]+separator+seriesPhog[contphog])
        if not os.path.exists(pathimgp):
            os.makedirs(pathimgp)
        req.urlretrieve(instances_url+imgp+'/preview', pathimgp+separator+imgp+".jpg")
        contphog = contphog + 1

#getImagesFromPacs()
listImg()
callParallelIndexer()
solrConnection()
getSimilarImagesPacs()