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import gradio as gr | |
import numpy as np | |
# load the trained CNN model | |
cnn_model = keras.models.load_model("fine_tuning.keras") | |
def Normal_or_Pneumonia(img): | |
img = img.reshape( -1, 180, 180,3 ) | |
prediction = cnn_model .predict(img).tolist()[0] | |
CLASS_NAMES = ["PNEUMONIA DETECTOR"] | |
return {CLASS_NAMES[i]: prediction[i] for i in range(1)} | |
#set the user uploaded image as the input array | |
#match same shape as the input shape in the model | |
image_input = gr.inputs.Image( shape=(180, 180) ,invert_colors=False , type="numpy" ) | |
#setup the interface | |
iface = gr.Interface( | |
fn = Normal_or_Pneumonia, | |
inputs = image_input, | |
outputs = gr.outputs.Label(), | |
) | |
iface.launch(share=True , debug = True) |