Create app.py

app.py

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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()