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loop_thread.py
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144 lines (128 loc) · 4.38 KB
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# from PIL import Image
# from propose import BBProposer
import threading
from circlepropose import Circle
import cv2
import numpy as np
from matting import BcRd
import time
import network
DEBUG = True
lastimg = None
end = False
CAMIDX = 4
class cap(threading.Thread):
def __init__(self):
global lastimg
threading.Thread.__init__(self)
self.camera = cv2.VideoCapture(CAMIDX)
ret, lastimg = self.camera.read()
print("INIT")
if not ret:
print("READ IMG ERROR")
def run(self):
global lastimg
while True:
ret, lastimg = self.camera.read()
if ret:
time.sleep(0.003)
else:
print("ERROR")
if end:
break
class Loop():
def __init__(self) -> None:
global lastimg
self.Predictor = Circle()
self.preimg = lastimg.copy()
if DEBUG:
cv2.imshow("ini_img", self.preimg)
cv2.waitKey(0)
if True:
self.pre_gray, self.pre_mask, self.pre_center = self.imgprocess(
self.preimg)
self.boarder = np.zeros(
(self.preimg.shape[0], self.preimg.shape[1]), dtype=np.uint8)
self.boarder[10:self.preimg.shape[0] -
10, 10:self.preimg.shape[1]-10] += 1
else:
print("Error! can not open camera!")
exit()
def imgprocess(self, img):
bb = self.Predictor.predict(img)
bbox = np.array(bb[0][0], dtype=int)
bg = BcRd(img)
mask = bg.GenMask(bbox)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
totalmask = np.zeros(gray.shape[0:2], dtype=np.uint8)
# totalmask[bbox[0]:bbox[2], bbox[1]:bbox[3]] = mask
totalmask[bbox[0]:bbox[2], bbox[1]:bbox[3]] = 1
totalmask[int((bbox[0]+bbox[2])/2), int((bbox[1]+bbox[3])/2)] = 0
if DEBUG:
cv2.imshow("mask", totalmask*250)
# (y, x)
return gray, totalmask, np.array([(bbox[1]+bbox[3])/2, (bbox[0]+bbox[2])/2])
def refresh(self, newimg, newgray, newmask):
self.preimg = newimg.copy()
self.pre_gray = newgray.copy()
self.pre_mask = newmask.copy()
def norm(self, vec):
if abs(vec[0]) > 0.01 or abs(vec[1]) > 0.01:
deno = max(abs(vec[0]), abs(vec[1]))*100
else:
deno = 1
return vec/deno
if __name__ == '__main__':
sender = network.Sender('192.168.137.187')
cam = cap()
cam.start()
mainloop = Loop()
while True:
st = time.time()
newimg = lastimg.copy()
ed = time.time()
print("cam= ", ed-st)
newgray, newmask, newcenter = mainloop.imgprocess(newimg)
if DEBUG:
overlap = np.array(mainloop.pre_gray*0.3 +
newgray*0.7, dtype=np.uint8)
cv2.imshow("overlap", overlap)
flow = cv2.calcOpticalFlowFarneback(
mainloop.pre_gray, newgray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
flow *= np.expand_dims(mainloop.pre_mask, 2).repeat(2, axis=2)
flow *= np.expand_dims(mainloop.boarder, 2).repeat(2, axis=2)
flowdata = flow.reshape(1, -1, 2)[0]
shift = np.mean(flowdata, axis=0) # (y_width, x_height)
move = (newcenter - mainloop.pre_center)/10000
shift /= 100
print("shift= ", shift)
print("move= ", move)
# nomalization
shift = mainloop.norm(shift)
move = mainloop.norm(move)
sender.sendvec(newcenter[0], newcenter[1])
print("center= ", newcenter)
'''
if abs(shift[0]) < 0.004 and abs(shift[1]) < 0.004:
if abs(move[0]) > 0.004 or abs(move[1]) > 0.004:
print("MOVE!")
# sender.sendvec(move[0], move[1])
sender.sendvec(newcenter[0], newcenter[1])
print("center= ", newcenter)
# mainloop.refresh(newimg, newgray, newmask)
pass
else:
print("CONVERGE!")
else:
print("SHIFT!")
# sender.sendvec(shift[0], shift[1])
sender.sendvec(newcenter[0], newcenter[1])
print("center= ", newcenter)
pass
'''
if cv2.waitKey(500) == 115:
end = True
break
ed = time.time()
print("t=", ed-st, "--------------------------")
cam.join()