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__author__ = "Baishali Dutta"
__copyright__ = "Copyright (C) 2021 Baishali Dutta"
__license__ = "Apache License 2.0"
__version__ = "0.1"
# -------------------------------------------------------------------------
# Importing the libraries
# -------------------------------------------------------------------------
import gradio as gr
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
# -------------------------------------------------------------------------
# Configurations
# -------------------------------------------------------------------------
MODEL_LOC = 'pneumonia_detection_cnn_model.h5'
# load the trained CNN model
cnn_model = load_model(MODEL_LOC)
def make_prediction(test_image):
test_image = test_image.name
test_image = image.load_img(test_image, target_size=(224, 224))
test_image = image.img_to_array(test_image) / 255.
test_image = np.expand_dims(test_image, axis=0)
result = cnn_model.predict(test_image)
return {"Normal": str(result[0][0]), "Pneumonia": str(result[0][1])}
image_input = gr.inputs.Image(type="file")
title = "Pneumonia Detection"
description = "This application uses a Convolutional Neural Network (CNN) model to predict whether a chosen X-ray shows if " \
"the person has pneumonia disease or not. To check the model prediction, here are the true labels of the " \
"provided examples below: the first 4 images belong to normal whereas the last 4 images are of pneumonia " \
"category. More specifically, the 5th and 6th images are viral pneumonia infection in nature whereas " \
"the last 2 images are bacterial infection in nature."
gr.Interface(fn=make_prediction,
inputs=image_input,
outputs="label",
examples=[["image1_normal.jpeg"],
["image2_normal.jpeg"],
["image3_normal.jpeg"],
["image4_normal.jpeg"],
["image1_pneumonia_virus.jpeg"],
["image2_pneumonia_virus.jpeg"],
["image1_pneumonia_bacteria.jpeg"],
["image2_pneumonia_bacteria.jpeg"]],
title=title,
description=description,
article="http://raw.githubusercontent.com/baishalidutta/Pneumonia-Detection/gradio/README.md") \
.launch(share=True)
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