| from tensorflow.keras.models import load_model | |
| import numpy as np | |
| import cv2 | |
| model = load_model('model-3.h5') | |
| def predict_from_img(img): | |
| img = cv2.cvtColor(img,cv2.COLOR_RGB2GRAY) | |
| img = img/255.0 | |
| img = np.expand_dims(img,axis = 0) | |
| output = model.predict(img)[0][0] | |
| return {'NORMAL':float(output),'PNEUMONIA':float(1-output)} | |
| import gradio as gr | |
| image = gr.inputs.Image(shape=(150,150)) | |
| label = gr.outputs.Label(num_top_classes=2) | |
| gr.Interface(fn=predict_from_img, inputs=image, outputs=label,title = 'PNEUMONIA-DETECTION').launch() |