Thank you Matthieu and everybody who showed interest in helping out with this issue. But I think I found a solution. Please find a small snippet of code which can be used when we have label data in this pixel coordinate format.
for k in range(len(image_paths)): #going through the folder where I have all the Images stored
image = plt.imread(path+image_paths[k]+".png") #reading the image
print(image_paths[k]+".png")
image=rgb2hed(image) #As the images are H&E - Hamotoxylin and Eosin stained images, we change it to this format (I also discovered about this while browsing some of this content on skimage) something new ;P
scipy.misc.imsave(os.path.join(path_train, image_paths[k]+".png"), image)
X_train.append(image[:,:,0:3])
height=image.shape[0]
width=image.shape[1]
patch = np.full((height,width),255)
#This is the part which helped me take those pixel values provided and create a patch like structure in the image.
f = open(path+image_paths[k]+".csv", "r")
for line in f:
lines=line.split()
pixels=lines[0].split(",")
for i in range(0,len(pixels),2): #putting 2, as 2 values denote x and y coordinate(lucky guess)
patch[int(pixels[i+1])][int(pixels[i])]=0
scipy.misc.imsave(os.path.join(path_label, image_paths[k]+".png"), patch) #saved it as a patch and it worked
Apologies if If the information provided in the first place was not that suffecient.
Regards,
Sahil