jphappy/Traffic_light_detection

1 2import gradio as gr3import numpy as np4from tensorflow.keras.models import load_model5from PIL import Image6 7model = load_model("traffic_light_model.keras")8 9class_names = [10    "Green Light",11    "Forward Arrow Green Light",12    "Left Turn Green Light",13    "Red Light",14    "Left Turn Red Light",15    "Yellow Light",16    "Yellow Left Turn Light"17]18 19def predict(image):20    img = Image.fromarray(image).resize((64, 64))21    img_array = np.array(img) / 255.022    img_array = np.expand_dims(img_array, axis=0)23    predictions = model.predict(img_array)[0]24    return {class_names[i]: float(predictions[i]) for i in range(len(class_names))}25 26demo = gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=3),27                    title="Traffic Light Detector")28demo.launch()29