|
|
|
@ -28,7 +28,6 @@ def main(): |
|
|
|
|
bin = cv2.medianBlur(bin, 3) |
|
|
|
|
contours, _ = cv2.findContours( bin.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) |
|
|
|
|
|
|
|
|
|
boxes = [] |
|
|
|
|
for cnt in contours: |
|
|
|
|
x, y, w, h = cv2.boundingRect(cnt) |
|
|
|
|
if h < 16 or h > 60 or 1.2*h < w: |
|
|
|
@ -44,7 +43,6 @@ def main(): |
|
|
|
|
if m00/255 < 0.1*w*h or m00/255 > 0.9*w*h: |
|
|
|
|
continue |
|
|
|
|
|
|
|
|
|
#frame[y:,x:][:h,:w] = sub[...,np.newaxis] |
|
|
|
|
c1 = np.float32([m['m10'], m['m01']]) / m00 |
|
|
|
|
c0 = np.float32([SZ/2, SZ/2]) |
|
|
|
|
t = c1 - s*c0 |
|
|
|
@ -53,17 +51,14 @@ def main(): |
|
|
|
|
A[:,2] = t |
|
|
|
|
sub1 = cv2.warpAffine(sub, A, (SZ, SZ), flags=cv2.WARP_INVERSE_MAP | cv2.INTER_LINEAR) |
|
|
|
|
sub1 = digits.deskew(sub1) |
|
|
|
|
if x+w+SZ < frame.shape[1] and y+SZ < frame.shape[0]: |
|
|
|
|
frame[y:,x+w:][:SZ, :SZ] = sub1[...,np.newaxis] |
|
|
|
|
|
|
|
|
|
sample = np.float32(sub1).reshape(1,SZ*SZ) / 255.0 |
|
|
|
|
digit = model.predict(sample)[0] |
|
|
|
|
|
|
|
|
|
cv2.putText(frame, '%d'%digit, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 0, 0), thickness = 1) |
|
|
|
|
|
|
|
|
|
boxes.append(sub1) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if len(boxes) > 0: |
|
|
|
|
cv2.imshow('box', mosaic(10, boxes)) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
cv2.imshow('frame', frame) |
|
|
|
|
cv2.imshow('bin', bin) |
|
|
|
|