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from keras.models import model_from_json |
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import cv2 |
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import numpy as np |
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class_names = ['Selfie','Non-Selfie'] |
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f = open("model_cnn1.json",'r+') |
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json_string = f.read() |
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f.close() |
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model = model_from_json(json_string) |
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model.load_weights('model_cnn1.h5') |
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model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) |
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def predict_image(img): |
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prediction = model.predict(img.reshape(-1,100,100,3))[0] |
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return {class_names[i]: float(prediction[i]) for i in range(2)} |
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import gradio as gr |
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image = gr.inputs.Image(shape=(100,100),label='Image To Classify') |
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label = gr.outputs.Label(label='Model thinks your image is') |
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gr.Interface(fn=predict_image, inputs=image, outputs=label,allow_flagging='never',title="Selfie Detection Web-App",description="Upload an image to check if it is a Selfie or not?").launch(debug='True') |
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