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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) |