inference_constant.py

#!/dls/science/groups/i23/scripts/chris/TFODCourse/tfod/bin/python

import tensorflow as tf
from tensorflow import keras
import cv2
from io import BytesIO
import urllib
from time import sleep
import numpy as np

model = tf.keras.models.load_model("final.h5")
model.summary()

def urltoimage(url):
    resp = urllib.request.urlopen(url)
    image = np.asarray(bytearray(resp.read()), dtype="uint8")
    image = cv2.imdecode(image, cv2.IMREAD_COLOR)
    image = image[400:700, 610:770]
    cv2.imwrite("tmp.jpg", image)
    _, buffer = cv2.imencode(".jpg", image)
    io_buf = BytesIO(buffer)
    return io_buf


def infer():
    stream = urltoimage("http://bl23i-di-serv-02.diamond.ac.uk:8080/ECAM6.mjpg.jpg")
    img_in = keras.preprocessing.image.load_img((stream), target_size=(300, 160))
    img_array = keras.preprocessing.image.img_to_array(img_in)
    img_array = tf.expand_dims(img_array, 0)
    predictions = model.predict(img_array, verbose=0)
    score = predictions[0]
    if score > 0.94:
        print("                                                  ", end="\r")
        print(f"{np.round((100 * score), 2)}% sure pin is ON", end="\r")
    elif score < 0.06:
        print("                                                  ", end="\r")
        print(f"{np.round((100 * (1 - score)), 2)}% sure pin is OFF", end="\r")
    else:
        print("                                                  ", end="\r")
        print("No idea if pin is off or on...", end="\r")


if __name__ == "__main__":
    while True:
        infer()
        sleep(0.5)