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Debug.py
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Debug.py
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from time import time
import cv2
import numpy as np
from Mosse_Tracker.TrackerManager import Tracker, TrackerType
from PIL import Image
#from Car_Detection_TF.yolo import YOLO
#from Car_Detection.detect import Yolo_image
from Mosse_Tracker.utils import draw_str
from boxes.yoloFiles import loadFile
pi=22/7
# clf = pickle.load(open('VIF/model-svm1.sav', 'rb'))
total_frames = []
counter_sub_video = 1
data = []
from VIF.vif import VIF
vif = VIF()
tracker_type = TrackerType.MOSSE
def predict(frames_RGB,trackers):
gray_frames = []
for frame in frames_RGB:
gray_frames.append(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))
no_crash = 0
crash = 0
for tracker in trackers:
tracker_frames,width,height,xmin,xmax,ymin,ymax = tracker.getFramesOfTracking(gray_frames)
if tracker_frames == None:
continue
# if xmax - xmin < 100:
# continue
#
# print("ymax"+str(ymax - ymin))
#
# print("xmax"+str(xmax - xmin))
#
# print("ymax/x"+str((ymax- ymin) / (xmax - xmin)))
if xmax - xmin < 50: #50
continue
if ymax - ymin <= 28: #35
continue
if (ymax- ymin) / (xmax - xmin) <0.35: #0.35
continue
feature_vec = vif.process(tracker_frames)
result = vif.clf.predict(feature_vec.reshape(1, 304))
if result[0] == 0.0:
no_crash += 1
else:
crash += 1
# trackers[0].saveTracking(frames_RGB)
# trackers[1].saveTracking(frames_RGB)
tracker.saveTracking(frames_RGB)
# print(crash, no_crash)
def checkDistance(frames,tracker_A,tracker_B,frame_no):
if not tracker_A.isAboveSpeedLimit(frame_no-10,frame_no) and not tracker_B.isAboveSpeedLimit(frame_no-10,frame_no) :
return False
xa, ya = tracker_A.estimationFutureCenter[frame_no]
xb, yb = tracker_B.estimationFutureCenter[frame_no]
r = pow(pow(xa - xb, 2) + pow(ya - yb, 2), 0.5)
tracker_A_area = 0.5 * tracker_A.width * tracker_A.height
tracler_B_area = 0.5 * tracker_B.width * tracker_B.height
# iou = intersectionOverUnion(tracker_A.tracker.getCutFramePosition((xa,ya)),tracker_B.tracker.getCutFramePosition((xb,yb)))
# iou2 = intersectionOverUnion(tracker_B.tracker.getCutFramePosition((xa, ya)),
# tracker_A.tracker.getCutFramePosition(tracker_A.tracker.center))
if tracker_type == TrackerType.MOSSE:
xa_actual,ya_actual = tracker_A.tracker.centers[frame_no]
xb_actual,yb_actual = tracker_B.tracker.centers[frame_no]
else:
xa_actual,ya_actual = tracker_A.get_position(tracker_A.history[frame_no])
xb_actual,yb_actual = tracker_B.get_position(tracker_B.history[frame_no])
difference_trackerA_actual_to_estimate = pow(pow(xa_actual - xa, 2) + pow(ya_actual - ya, 2), 0.5)
difference_trackerB_actual_to_estimate = pow(pow(xb_actual - xb, 2) + pow(yb_actual - yb, 2), 0.5)
max_difference = max(difference_trackerA_actual_to_estimate,difference_trackerB_actual_to_estimate)
# print(r,difference_trackerA_actual_to_estimate,difference_trackerB_actual_to_estimate,max_difference/r)
if r == 0:
return True
if r < 40 and max_difference/r > 0.5:
# print(r,difference_trackerA_actual_to_estimate,difference_trackerB_actual_to_estimate,max_difference/r)
return True
return False
def process(trackers,frames):
# predict(frames, trackers)
new_trackers = trackers
# for tracker in trackers:
# if tracker.isAboveSpeedLimit():
# new_trackers.append(tracker)
for i in range(len(new_trackers)):
for j in range(i+1,len(trackers)):
if i == j:
continue
tracker_A = trackers[i]
tracker_B = trackers[j]
if checkDistance(frames,tracker_A,tracker_B,16) or checkDistance(frames,tracker_A,tracker_B,19) or checkDistance(frames,tracker_A,tracker_B,22) or checkDistance(frames,tracker_A,tracker_B,25) or checkDistance(frames,tracker_A,tracker_B,28):
# tracker_A.saveTracking(frames)
# print("Maybe an accident has occured!")
predict(frames, [tracker_B,tracker_A])
class MainFlow:
def __init__(self, yolo, fromFile=True, select=False):
self.yolo = yolo
self.frameCount = 0
self.readFile = fromFile
# if select == False then use TF else use PYTORCH
self.selectYOLO = select
self.trackerId = 0
def run(self, path):
global total_frames
last_30_frames = []
last_delayed_30_frames = []
fileBoxes = []
new_frame = None
if self.readFile:
fileBoxes = loadFile(path)
# model = ''
# if self.selectYOLO:
# model = Darknet("Car_Detection/config/yolov3.cfg", CUDA=False)
# model.load_weight("Car_Detection/config/yolov3.weights")
cap = cv2.VideoCapture(path)
#frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
#frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
frame_width = 480
frame_height = 360
trackers = []
delayed_trackers = []
# run yolo every fps frames
fps = 30
hfps = 15
no_of_frames = 0
paused = False
cum_time = 0
while True:
if not paused:
t = time()
# read new frame
ret, frame = cap.read()
# if ret and no_of_frames <120:
# no_of_frames+=1
# continue
if ret:
dim = (480, 360)
frame = cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
#frame = cv2.GaussianBlur(frame, (-1, -1), 1.0) # 2.0
new_frame = frame.copy()
total_frames.append(new_frame)
# failed to get new frame
else:
break
# run ViF
if self.frameCount > 0 and (self.frameCount % fps == 0 or self.frameCount == fps - 1):
#print("FRAME " + str(self.frameCount) + " VIF")
#thread = Thread(target=predict(last_30_frames,trackers))
#thread.start()
#print("error")
#vif(trackers, frame_width, frame_height, frame)
t = time()
# thread = Thread(target=process(trackers,last_30_frames))
# thread.start()
process(trackers,last_30_frames)
print(time() - t)
if self.frameCount > 16 and self.frameCount % hfps == 0 and self.frameCount % fps != 0:
# print("FRAME " + str(self.frameCount) + " VIF")
# thread = Thread(target=predict(last_30_frames,trackers))
# thread.start()
# print("error")
# vif(trackers, frame_width, frame_height, frame)
t = time()
# thread = Thread(target=process(delayed_trackers, last_delayed_30_frames))
# thread.start()
#
process(delayed_trackers, last_delayed_30_frames)
print(time() - t)
if self.frameCount > 0 and self.frameCount % hfps == 0 and self.frameCount % fps != 0:
# print("YOLO CALLED in frame no. " + str(self.frameCount))
# clear earlier trackers
delayed_trackers = []
bboxes = []
last_delayed_30_frames = []
img = Image.fromarray(frame)
# detect vehicles
if self.readFile:
# From files
bboxes = fileBoxes[self.frameCount]
elif not self.selectYOLO:
# Khaled
img, bboxes = self.yolo.detect_image(img)
else:
# Roba
bboxes = Yolo_image(np.float32(img), model)
for i, bbox in enumerate(bboxes):
label = bbox[0]
# accuracy = bbox[5]
xmin = int(bbox[1])
xmax = int(bbox[2])
ymin = int(bbox[3])
ymax = int(bbox[4])
# can limit this part to cars and trucks only later
# cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), (0, 0, 255))
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
self.trackerId += 1
# no need for frame_width and frame_height
if xmax < frame_width and ymax < frame_height:
tr = Tracker(frame_gray, (xmin, ymin, xmax, ymax), frame_width, frame_height,
self.trackerId,tracker_type)
delayed_trackers.append(tr)
elif xmax < frame_width and ymax >= frame_height:
tr = Tracker(frame_gray, (xmin, ymin, xmax, frame_height - 1), frame_width, frame_height,
self.trackerId,tracker_type)
delayed_trackers.append(tr)
elif xmax >= frame_width and ymax < frame_height:
tr = Tracker(frame_gray, (xmin, ymin, frame_width - 1, ymax), frame_width, frame_height,
self.trackerId,tracker_type)
delayed_trackers.append(tr)
else:
tr = Tracker(frame_gray, (xmin, ymin, frame_width - 1, frame_height - 1), frame_width,
frame_height, self.trackerId,tracker_type)
delayed_trackers.append(tr)
else:
#print("updating trackers, frame no. " + str(self.frameCount) + "...")
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#print(len(trackers))
# updating trackers
for i, tracker in enumerate(delayed_trackers):
left, top, right, bottom = tracker.update(frame_gray)
# radian = tracker.getCarAngle() * (pi / 180)
# radian = 0
#
# #left = left * math.cos(radian) - top * math.sin(radian)
# #right = right * math.cos(radian) - bottom * math.sin(radian)
# #top = left * math.sin(radian) + top * math.cos(radian)
# #bottom = right * math.sin(radian) + bottom * math.cos(radian)
#
left_future, top_future, right_future, bottom_future = tracker.futureFramePosition()
#
# if left > 0 and top > 0 and right < frame_width and bottom < frame_height:
# if tracker.isAboveSpeedLimit():
# cv2.rectangle(frame, (int(left), int(top)),(int(right), int(bottom)), (0, 0, 255)) #B G R
# else:
# cv2.rectangle(frame, (int(left), int(top)),(int(right), int(bottom)), (255, 0, 0))
#
#
#
#
# #draw_str(frame, (left, bottom + 64), 'Max Speed: %.2f' % tracker.getMaxSpeed())
# #draw_str(frame, (left, bottom + 16), 'Avg Speed: %.2f' % tracker.getAvgSpeed())
# #draw_str(frame, (left, bottom + 96), 'Cur Speed: %.2f' % tracker.getCurrentSpeed())
# #draw_str(frame, (left, bottom + 112), 'Area Size: %.2f' % tracker.getCarSizeCoefficient())
# #draw_str(frame, (left, bottom + 32), 'Moving Angle: %.2f' % tracker.getCarAngle())
#
# if left_future > 0 and top_future > 0 and right_future < frame_width and bottom_future < frame_height:
# cv2.rectangle(frame, (int(left_future), int(top_future)), (int(right_future), int(bottom_future)), (0, 255, 0))
# Call YOLO
if self.frameCount % fps == 0 or self.frameCount == 0:
#print("YOLO CALLED in frame no. " + str(self.frameCount))
# clear earlier trackers
trackers = []
bboxes = []
last_30_frames = []
img = Image.fromarray(frame)
# detect vehicles
if self.readFile:
# From files
bboxes = fileBoxes[self.frameCount]
elif not self.selectYOLO:
# Khaled
img, bboxes = self.yolo.detect_image(img)
else:
# Roba
bboxes = Yolo_image(np.float32(img), model)
for i, bbox in enumerate(bboxes):
label = bbox[0]
# accuracy = bbox[5]
xmin = int(bbox[1])
xmax = int(bbox[2])
ymin = int(bbox[3])
ymax = int(bbox[4])
# can limit this part to cars and trucks only later
# cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), (0, 0, 255))
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
self.trackerId +=1
# no need for frame_width and frame_height
if xmax < frame_width and ymax < frame_height:
tr = Tracker(frame_gray, (xmin, ymin, xmax, ymax), frame_width, frame_height,self.trackerId,tracker_type)
trackers.append(tr)
elif xmax < frame_width and ymax >= frame_height:
tr = Tracker(frame_gray, (xmin, ymin, xmax, frame_height - 1), frame_width, frame_height,self.trackerId,tracker_type)
trackers.append(tr)
elif xmax >= frame_width and ymax < frame_height:
tr = Tracker(frame_gray, (xmin, ymin, frame_width - 1, ymax), frame_width, frame_height,self.trackerId,tracker_type)
trackers.append(tr)
else:
tr = Tracker(frame_gray, (xmin, ymin, frame_width - 1, frame_height - 1), frame_width, frame_height,self.trackerId,tracker_type)
trackers.append(tr)
else:
#print("updating trackers, frame no. " + str(self.frameCount) + "...")
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#print(len(trackers))
# updating trackers
for i, tracker in enumerate(trackers):
left, top, right, bottom = tracker.update(frame_gray)
radian = tracker.getCarAngle() * (pi / 180)
radian = 0
#left = left * math.cos(radian) - top * math.sin(radian)
#right = right * math.cos(radian) - bottom * math.sin(radian)
#top = left * math.sin(radian) + top * math.cos(radian)
#bottom = right * math.sin(radian) + bottom * math.cos(radian)
left_future, top_future, right_future, bottom_future = tracker.futureFramePosition()
if left > 0 and top > 0 and right < frame_width and bottom < frame_height:
if tracker.isAboveSpeedLimit():
cv2.rectangle(frame, (int(left), int(top)),(int(right), int(bottom)), (0, 0, 255)) #B G R
else:
cv2.rectangle(frame, (int(left), int(top)),(int(right), int(bottom)), (255, 0, 0))
#draw_str(frame, (left, bottom + 64), 'Max Speed: %.2f' % tracker.getMaxSpeed())
draw_str(frame, (left, bottom + 16), 'Avg Speed: %.2f' % tracker.getAvgSpeed())
#draw_str(frame, (left, bottom + 96), 'Cur Speed: %.2f' % tracker.getCurrentSpeed())
#draw_str(frame, (left, bottom + 112), 'Area Size: %.2f' % tracker.getCarSizeCoefficient())
#draw_str(frame, (left, bottom + 32), 'Moving Angle: %.2f' % tracker.getCarAngle())
if left_future > 0 and top_future > 0 and right_future < frame_width and bottom_future < frame_height:
cv2.rectangle(frame, (int(left_future), int(top_future)), (int(right_future), int(bottom_future)), (0, 255, 0))
# sleep(0.02)
#cv2.namedWindow("result", cv2.WINDOW_NORMAL)
cum_time += time() - t
cv2.imshow("result", frame)
last_30_frames.append(new_frame)
last_delayed_30_frames.append(new_frame)
if self.frameCount %fps == 0:
print(self.frameCount/cum_time)
# increment number of frames
self.frameCount += 1
ch = cv2.waitKey(10)
if ch == ord(' '):
paused = not paused
print(self.trackerId)
if __name__ == '__main__':
# m = MainFlow(None, select=False)
# m.run('videos/1500.mp4')
m = MainFlow(None, select=False)
# m.run('videos/1508.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1516.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1521.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1528.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1529.mp4')
# m = MainFlow(None, select=False)
m.run('videos/1533.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1534.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/Easy.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1559.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1563.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1566.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1537.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1506.mp4')
# m = MainFlow(None, select=False) #but have issue in the yolo file
# m.run('videos/1513.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1518.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1528.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1543.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1503.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1517.mp4')
#
m = MainFlow(None, select=False)
# m.run('videos/1601.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1561.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1562.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1564.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/1565.mp4')
# m = MainFlow(None, select=False)
# m.run('videos/normal1.mp4')
# for i in range(1543,1545):
# print("F")
# m = MainFlow(None, select=False)
# m.run('videos/'+str(i)+'.mp4')