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recognise.py
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recognise.py
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import cv2
import numpy as np
def nothing(x):
pass
image_x, image_y = 64,64
from keras.models import load_model
classifier = load_model('Trained_model.h5')
def predictor():
import numpy as np
from keras.preprocessing import image
test_image = image.load_img('1.png', target_size=(64, 64))
test_image = image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis = 0)
result = classifier.predict(test_image)
if result[0][0] == 1:
return 'A'
elif result[0][1] == 1:
return 'B'
elif result[0][2] == 1:
return 'C'
elif result[0][3] == 1:
return 'D'
elif result[0][4] == 1:
return 'E'
elif result[0][5] == 1:
return 'F'
elif result[0][6] == 1:
return 'G'
elif result[0][7] == 1:
return 'H'
elif result[0][8] == 1:
return 'I'
elif result[0][9] == 1:
return 'J'
elif result[0][10] == 1:
return 'K'
elif result[0][11] == 1:
return 'L'
elif result[0][12] == 1:
return 'M'
elif result[0][13] == 1:
return 'N'
elif result[0][14] == 1:
return 'O'
elif result[0][15] == 1:
return 'P'
elif result[0][16] == 1:
return 'Q'
elif result[0][17] == 1:
return 'R'
elif result[0][18] == 1:
return 'S'
elif result[0][19] == 1:
return 'T'
elif result[0][20] == 1:
return 'U'
elif result[0][21] == 1:
return 'V'
elif result[0][22] == 1:
return 'W'
elif result[0][23] == 1:
return 'X'
elif result[0][24] == 1:
return 'Y'
elif result[0][25] == 1:
return 'Z'
cam = cv2.VideoCapture(0)
cv2.namedWindow("Trackbars")
cv2.createTrackbar("L - H", "Trackbars", 0, 179, nothing)
cv2.createTrackbar("L - S", "Trackbars", 0, 255, nothing)
cv2.createTrackbar("L - V", "Trackbars", 0, 255, nothing)
cv2.createTrackbar("U - H", "Trackbars", 179, 179, nothing)
cv2.createTrackbar("U - S", "Trackbars", 255, 255, nothing)
cv2.createTrackbar("U - V", "Trackbars", 255, 255, nothing)
cv2.namedWindow("test")
img_counter = 0
img_text = ''
while True:
ret, frame = cam.read()
frame = cv2.flip(frame,1)
l_h = cv2.getTrackbarPos("L - H", "Trackbars")
l_s = cv2.getTrackbarPos("L - S", "Trackbars")
l_v = cv2.getTrackbarPos("L - V", "Trackbars")
u_h = cv2.getTrackbarPos("U - H", "Trackbars")
u_s = cv2.getTrackbarPos("U - S", "Trackbars")
u_v = cv2.getTrackbarPos("U - V", "Trackbars")
img = cv2.rectangle(frame, (425,100),(625,300), (0,255,0), thickness=2, lineType=8, shift=0)
lower_blue = np.array([l_h, l_s, l_v])
upper_blue = np.array([u_h, u_s, u_v])
imcrop = img[102:298, 427:623]
hsv = cv2.cvtColor(imcrop, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lower_blue, upper_blue)
cv2.putText(frame, img_text, (30, 400), cv2.FONT_HERSHEY_TRIPLEX, 1.5, (0, 255, 0))
cv2.imshow("test", frame)
cv2.imshow("mask", mask)
#if cv2.waitKey(1) == ord('c'):
img_name = "1.png"
save_img = cv2.resize(mask, (image_x, image_y))
cv2.imwrite(img_name, save_img)
print("{} written!".format(img_name))
img_text = predictor()
if cv2.waitKey(1) == 27:
break
cam.release()
cv2.destroyAllWindows()