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viral_bacterial.py
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viral_bacterial.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Feb 27 11:32:49 2021
Code base from https://www.kaggle.com/madz2000/pneumonia-detection-using-cnn-92-6-accuracy
@author: Aaron Gregory
"""
from keras.models import model_from_json
import numpy
from PIL import Image
class_names = ["Pneumonia", "Normal"]
# load json and create model
json_file = open('../weights/viral_bacterial.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
# load weights into new model
loaded_model.load_weights("../weights/viral_bacterial.h5")
def is_normal(xray_img):
"""
Returns 1 if xray_img shows a healthy xray, 0 else
"""
resized = xray_img.resize((150, 150))
open_cv_image = numpy.array(resized.convert('L')) / 255
open_cv_image = open_cv_image.reshape(-1,150,150,1)
output = loaded_model.predict_classes(open_cv_image)
return output[0,0]
if __name__ == "__main__":
image = Image.open("./c0.png")
print(class_names[is_normal(image)])
image = Image.open("./c1.png")
print(class_names[is_normal(image)])
image = Image.open("./n0.png")
print(class_names[is_normal(image)])
image = Image.open("./n1.png")
print(class_names[is_normal(image)])
image = Image.open("./v0.png")
print(class_names[is_normal(image)])
image = Image.open("./v1.png")
print(class_names[is_normal(image)])