BrandedYeoh123/Food-Scanner-AI

1import gradio as gr2import tensorflow as tf3import numpy as np4from PIL import Image5 6# Load the trained model7import tensorflow as tf8 9model = tf.keras.models.load_model("keras_model.h5", compile=False)10 11# Manually compile the model12model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])  # Ensure you upload model.h513 14labels = ["Pizza", "Burger", "Salad", "Pasta"]  # Update with your food classes15 16def predict_image(img):17    from PIL import Image18    import numpy as np19 20    if isinstance(img, np.ndarray):21        img = Image.fromarray(img)  # Convert NumPy array to PIL Image22 23    img = img.convert("RGB")  # Convert image to RGB24    img = img.resize((224, 224))  # Resize for the model25    img_array = np.array(img) / 255.0  # Normalize26    img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension27 28    prediction = model.predict(img_array)29    return {labels[i]: float(prediction[0][i]) for i in range(len(labels))}30 31interface = gr.Interface(fn=predict_image, inputs="image", outputs="label")32interface.launch(share=True)33