import cv2
import pandas as pd
import os
import numpy

img_folder_path='/media/sadam/44C611803928605D/Downloads/ChestXray-NIHCC/a/00000003_000.png'
frame=cv2.imread(img_folder_path)

ac_bbox = '/home/sadam/CheXNet-with-localization/output/bounding_box.txt'
pd_bbox = '/home/sadam/CheXNet-with-localization/bounding_box.txt'

def plot_bbox(img_folder_path, bbox_filename):
    actual_bbox=open(bbox_filename)
    img_folder_path=os.path.split(img_folder_path)[-1]
    #print(img_folder_path)
    count=0
    temp_count=0
    final_bbox_list=[]
    for img in actual_bbox :
        if img.find(img_folder_path) != -1:
            print('file exist:',count)
            print('given image',img)
            temp_count=count
            print("this is temp count",temp_count)
        if count > temp_count:

            if img.find('/') == -1 :
                final_bbox_list.append(img)
            else:
                break
        count+=1

    i=final_bbox_list[1]
    temp_i=list(i.split(" "))
    temp_i.pop(0)

    p = numpy.array(temp_i)
    k=p.astype(float)

    x1=int(k[0])
    y1=int(k[1])
    x2=int(k[2])
    y2=int(k[3])
    return x1,y1,x2,y2

x1,y1,x2,y2=plot_bbox(img_folder_path, ac_bbox)
x_1,y_1,x_2,y_2=plot_bbox(img_folder_path, pd_bbox)

cv2.rectangle(frame,(x1,y1),(x2,y2),(0,255,0),3) #rgb 220,20,60
cv2.rectangle(frame,(x_1,y_1),(x_2,y_2),(60,20,220),3)
print(frame)
cv2.imshow('image',frame)
cv2.waitKey(0)
cv2.destroyAllWindows()

@rajdeinno I know the code is very roughly patched but it does the job. It takes an image input , checks if it's bboxes are defined in bbox actual file then draws boxed regions (predicted and actual ones). This code only draws bbox of first class of an input images. You can add further checks to work it for all class labels.

how to visualise the bounding_box.txt file in an image? #9

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