detect.py

import cv2
import numpy as np
from keras.models import load_model
import cvzone

np.set_printoptions(suppress=True)

model = load_model('keras_model.h5', compile=False)

class_names = ['Nao esta fumando', 'Esta fumando']

img = cv2.imread('Test/not_smoking/avatar_cv.png')

while True:

    image = cv2.resize(img, (224, 224), interpolation=cv2.INTER_AREA)
    image = np.asarray(image, dtype=np.float32).reshape(1, 224, 224, 3)
    image = (image / 127.5) - 1

    prediction = model.predict(image)
    index = np.argmax(prediction)
    class_name = class_names[index]
    confidence_score = prediction[0][index]

    texto1 = f"Classe: {class_name}"
    texto2 = f"Taxa de acerto: {str(np.round(confidence_score * 100))[:-2]} %"

    cvzone.putTextRect(img, texto1, (50, 50), scale=3)
    cvzone.putTextRect(img, texto2, (50, 100), scale=3)

    cv2.imshow('Detector de Fumante', img)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

img.release()
cv2.destroyAllWindows()