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import cv2
import numpy as np
from keras.models import load_model
# Load the model
model = load_model('keras_model.h5')
# CAMERA can be 0 or 1 based on default camera of your computer.
camera = cv2.VideoCapture(0)
# Grab the labels from the labels.txt file. This will be used later.
labels = open('labels.txt', 'r').readlines()
while True:
# Grab the webcameras image.
ret, image = camera.read()
# Resize the raw image into (224-height,224-width) pixels.
image = cv2.resize(image, (224, 224), interpolation=cv2.INTER_AREA)
# Show the image in a window
cv2.imshow('Webcam Image', image)
# Make the image a numpy array and reshape it to the models input shape.
image = np.asarray(image, dtype=np.float32).reshape(1, 224, 224, 3)
# Normalize the image array
image = (image / 127.5) - 1
# Have the model predict what the current image is. Model.predict
# returns an array of percentages. Example:[0.2,0.8] meaning its 20% sure
# it is the first label and 80% sure its the second label.
probabilities = model.predict(image)
# Print what the highest value probabilitie label
print(labels[np.argmax(probabilities)])
# Listen to the keyboard for presses.
keyboard_input = cv2.waitKey(1)
# 27 is the ASCII for the esc key on your keyboard.
if keyboard_input == 27:
break
camera.release()
cv2.destroyAllWindows()
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