return True
else:
return False
def wrap_digit(rect):
x,y,w,h=rect
padding=5
hcenter=x+w/2
vcenter=y+h/2
if(h>w):
w=h
x=hcenter-(w/2)
else:
h=w
y=vcenter=(h/2)
return x - padding, y - padding, w + padding, h + padding
ann ,test_data=ANN.train(ANN.create_ANN(56),20000)
font = cv2.FONT_HERSHEY_SIMPLEX
path="images/numbers.jpg"
img=cv2.imread(path,cv2.IMREAD_UNCHANGED)
bw =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
bw=cv2.GaussianBlur(bw,(7,7),0)
ret,thbw=cv2.threshold(bw,127,255,cv2.THRESH_BINARY_INV)
thbw=cv2.erode(thbw,np.ones((2,2),np.uint8),interations=2)
image,cntrs,hier=cv2.findContours(thbw.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
rectangles =[]
for c in cntrs:
r=x,y,w,h=cv2.boundingRect(c)
a=cv2.contourArea(c)
def wrap_digit(rect):
x, y, w, h = rect
padding = 5
hcenter = x + w/2
vcenter = y + h/2
roi = None
if (h > w):
w = h
x = hcenter - (w/2)
else:
h = w
y = vcenter - (h/2)
return (x-padding, y-padding, w+padding, h+padding)
# ann, test_data = ANN.train(ANN.create_ANN(56), 50000, 5)
ann, test_data = ANN.train(ANN.create_ANN(58), 50000, 5)
font = cv2.FONT_HERSHEY_SIMPLEX
# path = "./images/MNISTsamples.png"
path = "./images/numbers.jpg"
img = cv2.imread(path, cv2.IMREAD_UNCHANGED)
bw = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
bw = cv2.GaussianBlur(bw, (7,7), 0)
ret, thbw = cv2.threshold(bw, 127, 255, cv2.THRESH_BINARY_INV)
thbw = cv2.erode(thbw, np.ones((2,2), np.uint8), iterations = 2)
image, cntrs, hier = cv2.findContours(thbw.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
rectangles = []
for c in cntrs:
r = x,y,w,h = cv2.boundingRect(c)
roi = None
if (h > w):
w = h
x = hcenter - (w // 2)
else:
h = w
y = vcenter - (h // 2)
padding = 5
x -= padding
y -= padding
w += 2 * padding
h += 2 * padding
return x, y, w, h
ann, test_data = ANN.train(ANN.create_ANN(60), 50000, 10)
font = cv2.FONT_HERSHEY_SIMPLEX
img_path = "./digit_images/digits_0.jpg"
img = cv2.imread(img_path, cv2.IMREAD_COLOR)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.GaussianBlur(gray, (7, 7), 0, gray)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
erode_kernel = np.ones((2, 2), np.uint8)
thresh = cv2.erode(thresh, erode_kernel, thresh, iterations=2)
if OPENCV_MAJOR_VERSION >= 4:
# OpenCV 4 or a later version is being used.
def wrap_digit(rect):
x, y, w, h = rect
padding = 5
hcenter = x + w / 2
vcenter = y + h / 2
if (h > w):
w = h
x = hcenter - (w / 2)
else:
h = w
y = vcenter - (h / 2)
return (x - padding, y - padding, w + padding, h + padding)
ann, test_data = ANN.train(ANN.create_ANN(56), 20000)
font = cv2.FONT_HERSHEY_SIMPLEX
path = "numbers.png"
img = cv2.imread(path, cv2.IMREAD_UNCHANGED)
bw = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
bw = cv2.GaussianBlur(bw, (7, 7), 0)
ret, thbw = cv2.threshold(bw, 200, 255, cv2.THRESH_BINARY_INV)
thbw = cv2.erode(thbw, np.ones((1, 1), np.uint8), iterations=2)
image, cntrs, hier = cv2.findContours(thbw.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
rectangles = []
for c in cntrs:
r = x, y, w, h = cv2.boundingRect(c)