import sys

from glob import glob

from PIL import Image

%matplotlib inline

from matplotlib import pyplot as plt

import os

import cv2

import json

import pandas as pd

import numpy as np

from glob import glob 

from tqdm import tqdm

from IPython import embed

import base64

import csv

from tqdm import trange

import xml.etree.cElementTree as ET

# from labelme import utils

if sys.version_info[0] == 2:

    import xml.etree.cElementTree as ET

else:

    import xml.etree.ElementTree as ET

font = cv2.FONT_HERSHEY_SIMPLEX

color_mode = [(0,0,255),(0,255,0),(255,0,0),(0,255,255),(255,0,255),(255,255,0),(255,255,255)]

plt.figure(figsize=(10, 10))

image_path = r"G:\bleeding\labelled_images\blood_fresh\Blood - fresh"

csv_file = r"G:\bleeding\metadata.csv"

csvfile = open( r"G:\bleeding\metadata.csv",'r')

annotations = [each for each in csv.DictReader(csvfile, delimiter=';')]

# annotations = pd.read_csv(csv_file,header=None).values

# category = reader['finding_category']

img_name = os.listdir(image_path)

total_csv_annotations = []

total_position = []

for annotation in annotations:

    key = annotation['filename']#.split(os.sep)[-1]

    # name = annotation['filename']

    position = [annotation['x1'],annotation['y1'],annotation['x2'],annotation['y2'],annotation['x3'],

    annotation['y3'],annotation['x4'],annotation['y4']]

    name = key

    if key in img_name:

        pts = ['xmin', 'ymin', 'xmax', 'ymax']

        bndbox = [min(position[0],position[2],position[4],position[6]),min(position[1],position[3],position[5],position[7]),

                max(position[0],position[2],position[4],position[6]),max(position[1],position[3],position[5],position[7])]

        img = cv2.imread(os.path.join(image_path,key))

        top_corner, down_corner = (int(bndbox[0]), int(bndbox[1])), (int(bndbox[2]), int(bndbox[3]))

        cv2.rectangle(img, top_corner, down_corner, color_mode[0], thickness=2)

        # cv2.putText(img,str(name),(top_corner[0]+5, top_corner[1]+25), font, 1,color_mode[1],1,cv2.LINE_AA)       

        plt.imshow(img[:,:,::-1])

        plt.axis('off')

        plt.show()