def getGestureImg(cnt, img, th1, model):
x, y, w, h = cv2.boundingRect(cnt)
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
imgT = img[y:y + h, x:x + w]
imgT = cv2.bitwise_and(imgT, imgT, mask=th1[y:y + h, x:x + w])
imgT = cv2.resize(imgT, (200, 200))
imgTG = cv2.cvtColor(imgT, cv2.COLOR_BGR2GRAY)
resp = st.predict(model, imgTG)
img = cv2.imread('TrainData\\' + chr(int(resp[1]) + 64) + '_2.jpg')
return img, chr(int(resp[1]) + 64)
def getGestureImg(cnt,img,th1,model):
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
img_gray = cv2.cvtColor(img[y:y+h,x:x+w], cv2.COLOR_BGR2GRAY)
img_gray_inv = 255 - img_gray
img_blur = cv2.GaussianBlur(img_gray_inv, ksize=(21, 21),sigmaX=0, sigmaY=0)
imgT = dodgeV2(img_gray, img_blur)
imgT=cv2.bitwise_and(imgT,imgT,mask=th1[y:y+h,x:x+w])
imgT=cv2.resize(imgT,(200,200))
resp=st.predict(model,imgT)
img=cv2.imread('DB/'+chr(int(resp[0])+64)+'_2.jpg')
return img,chr(int(resp[0])+64)
pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 15)
pipeline.start(config)
try:
while True:
frames = pipeline.wait_for_frames()
color_frame = frames.get_color_frame()
if not color_frame:
continue
# Convert realsense images to numpy arrays
color_image = np.asanyarray(color_frame.get_data())
#color_image = color_image[300:700, 300:500]
cv2.imshow('Result', color_image)
key = cv2.waitKey(10)
if key == ord('s'):
color_image = st.predict(color_image)
cv2.imshow("Result", color_image)
cv2.waitKey()
if key == ord('e'):
break
finally:
pipeline.stop()
