--- a
+++ b/read_detection.py
@@ -0,0 +1,57 @@
+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()