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| from PIL import Image | |
| import numpy as np | |
| import gradio as gr | |
| import keras | |
| model = keras.models.load_model('CATvsDOG.keras') | |
| def classify_image(image): | |
| img = Image.open(image) | |
| # Preprocess the image | |
| img = img.resize((100, 100)) | |
| img_array = np.array(img) | |
| img_array = np.expand_dims(img_array, axis=0) | |
| # Make predictions | |
| predictions = model.predict(img_array) | |
| if predictions[0][0] > 0.5: | |
| return "Dog" | |
| else: | |
| return "Cat" | |
| interface = gr.Interface(fn=classify_image, inputs="file", outputs="label", title="Cat or Dog Classifier") | |
| interface.launch(share=True) |