yagna08/Traffic-Sign-Detection

1import gradio as gr2import numpy as np3import pandas as pd4import tensorflow as tf5import cv26 7def grayScale(image):8    image = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)9    return image10 11def equalizer(image):12    image = cv2.equalizeHist(image)13    return image14 15def preprocessing(image):16    image = grayScale(image)17    image = equalizer(image)18    image = image/25519    return image20 21def classify_image(inp):22    print(inp.shape)23    inp = np.asarray(inp)24    print(inp.shape)25    inp = cv2.resize(inp, (64, 64))26    inp = preprocessing(inp)27    print(inp.shape)28    inp=inp.reshape(-1,inp.shape[0],inp.shape[1],1)29 30    model = tf.keras.models.load_model('final.h5')31    df = pd.read_csv('traffic_sign.csv')32    pred = model.predict(inp)33    print(pred[0])34    print(np.max(pred[0]))35    return df.loc[np.argmax(pred[0]),'Name']36    # return df.loc[pred,'Name']37 38gr.Interface(fn=classify_image,39             inputs=gr.Image(label='Upload a photo'),40             outputs=gr.Label(label='Predicted Traffic Sign'),41             examples=['giveway.png','dip.jpeg'],42             title='Traffic Sign Detection',43             theme='dark'44             ).launch(share=True)45 46 47