def predictMask(path):
pspnet = PSPNet()
image = Image.open(path)
start = time.process_time()
r_image = pspnet.detect_image(image)
end = time.process_time()
print('Running time: %s Seconds' % (end - start))
r_image.save(path)
#-------------------------------------#
# 调用摄像头
# capture=cv2.VideoCapture("1.mp4")
#-------------------------------------#
capture=cv2.VideoCapture(0)
fps = 0.0
while(True):
t1 = time.time()
# 读取某一帧
ref,frame=capture.read()
# 格式转变，BGRtoRGB
frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
# 转变成Image
frame = Image.fromarray(np.uint8(frame))
# 进行检测
frame = np.array(pspnet.detect_image(frame))
# RGBtoBGR满足opencv显示格式
frame = cv2.cvtColor(frame,cv2.COLOR_RGB2BGR)
fps = ( fps + (1./(time.time()-t1)) ) / 2
print("fps= %.2f"%(fps))
frame = cv2.putText(frame, "fps= %.2f"%(fps), (0, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.imshow("video",frame)
c= cv2.waitKey(30) & 0xff
if c==27:
capture.release()
break
4、如果想根据mask获取对应的区域，可以参考detect_image函数中，利用预测结果绘图的部分，判断每一个像素点的种类，然后根据种类获取对应的部分。
seg_img = np.zeros((np.shape(pr)[0],np.shape(pr)[1],3))
for c in range(self.num_classes):
seg_img[:, :, 0] += ((pr == c)*( self.colors[c][0] )).astype('uint8')
seg_img[:, :, 1] += ((pr == c)*( self.colors[c][1] )).astype('uint8')
seg_img[:, :, 2] += ((pr == c)*( self.colors[c][2] )).astype('uint8')
'''
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = pspnet.detect_image(image)
r_image.show()
elif mode == "video":
capture = cv2.VideoCapture(video_path)
if video_save_path != "":
fourcc = cv2.VideoWriter_fourcc(*'XVID')
size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
out = cv2.VideoWriter(video_save_path, fourcc, video_fps, size)
ref, frame = capture.read()
if not ref:
raise ValueError("未能正确读取摄像头（视频），请注意是否正确安装摄像头（是否正确填写视频路径）。")
fps = 0.0
#-------------------------------------#
# 对单张图片进行预测
#-------------------------------------#
from pspnet import PSPNet
from PIL import Image
import time
pspnet = PSPNet()
while True:
img = input('Input image filename:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
start = time.process_time()
#中间写上代码块
r_image = pspnet.detect_image(image)
end = time.process_time()
print('Running time: %s Seconds' % (end - start))
r_image.show()
