img_h, img_w = img.shape[:2]
img_area = img_w * img_h
for c in contours:
a = cv2.contourArea(c)
if a >= 0.98 * img_area or a <= 0.0001 * img_area:
continue
r = cv2.boundingRect(c)
is_inside = False
for q in rectangles:
if inside(r, q):
is_inside = True
break
if not is_inside:
rectangles.append(r)
for r in rectangles:
x, y, w, h = wrap_digit(r, img_w, img_h)
roi = thresh[y:y+h, x:x+w]
digit_class = int(digits_ann.predict(ann, roi)[0])
cv2.rectangle(img, (x,y), (x+w, y+h), (255, 0, 0), 2)
cv2.putText(img, "%d" % digit_class, (x, y-5),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
cv2.imwrite("detected_and_classified_digits_thresh.png", thresh)
cv2.imwrite("detected_and_classified_digits.png", img)
cv2.imshow("thresh", thresh)
cv2.imshow("detected and classified digits", img)
cv2.waitKey()
for c in contours:
a = cv2.contourArea(c)
if a >= 0.98 * img_area or a <= 0.0001 * img_area:
continue
r = cv2.boundingRect(c)
is_inside = False
for q in rectangles:
if inside(r, q):
is_inside = True
break
if not is_inside:
rectangles.append(r)
for r in rectangles:
x, y, w, h = wrap_digit(r)
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
roi = thresh[y:y + h, x:x + w]
try:
digit_class = int(ANN.predict(ann, roi)[0])
except:
continue
cv2.putText(img, "%d" % digit_class, (x, y - 1), font, 1, (0, 255, 0))
cv2.imshow("thresh", thresh)
cv2.imshow("detected and classified digits", img)
cv2.imwrite("detected_and_classified_digits.png", img)
cv2.waitKey()
rectangles =[]
for c in cntrs:
r=x,y,w,h=cv2.boundingRect(c)
a=cv2.contourArea(c)
b=(img.shape[0]-2) *(img.shape[1]-3)
is_inside = False
for q in rectangles:
if inside(r,q):
is_inside=True
break
if not is_inside:
if not a == b:
rectangles.append(r)
for r in rectangles:
x,y,w,h=wrap_digit(r)
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
roi=thbw[y:y+h,x:x+w]
try:
digit_class=int(ANN.predict(ann,roi.cope())[0])
except:
continue
cv2.putText(img,"%d" %digit_class,(x,y-1),font,1,(0,255,0))
cv2.imshow("thbw",thbw)
cv2.imshow("countours",img)
cv2.imwrite("sample.jpg",img)
cv2.waitKey()
b = (img.shape[0] - 3) * (img.shape[1] - 3)
is_inside = False
for q in rectangles:
if inside(r, q):
is_inside = True
break
if not is_inside:
if not a == b:
rectangles.append(r)
for r in rectangles:
x, y, w, h = wrap_digit(r)
x = int(x)
y = int(y)
w = int(w)
h = int(h)
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
roi = thbw[y:y + h, x:x + h]
try:
digital_class = int(ANN.predict(ann, roi.copy())[0])
except:
continue
cv2.putText(img, "%d" % digital_class, (x, y - 1), font, 1, (0, 255, 0))
cv2.namedWindow("thbw", 0)
cv2.resizeWindow("thbw", 640, 480)
cv2.imshow("thbw", thbw)
cv2.namedWindow("counters", 0)
cv2.resizeWindow("counters", 640, 480)
cv2.imshow("counters", img)
cv2.imwrite("sample.jpg", img)
cv2.waitKey()