120 lines
3.9 KiB
Python
120 lines
3.9 KiB
Python
from imutils.video import VideoStream
|
|
import argparse
|
|
import datetime
|
|
import imutils
|
|
import time
|
|
import cv2
|
|
import os
|
|
import traceback
|
|
import _thread
|
|
import imageio
|
|
import numpy as np
|
|
import time
|
|
from threading import Thread
|
|
from multiprocessing import Queue, Process, Pool
|
|
from multiprocessing.pool import ThreadPool
|
|
import concurrent.futures
|
|
from VideoReader import VideoReader
|
|
|
|
class ContourExtractor:
|
|
|
|
#X = {frame_number: [(contour, (x,y,w,h)), ...], }
|
|
extractedContours = dict()
|
|
min_area = 500
|
|
max_area = 28000
|
|
threashold = 13
|
|
xDim = 0
|
|
yDim = 0
|
|
|
|
def getextractedContours(self):
|
|
return self.extractedContours
|
|
|
|
def __init__(self):
|
|
print("ContourExtractor initiated")
|
|
|
|
def extractContours(self, videoPath, resizeWidth):
|
|
firstFrame = None
|
|
extractedContours = dict()
|
|
videoReader = VideoReader(videoPath)
|
|
self.xDim = videoReader.w
|
|
self.yDim = videoReader.h
|
|
videoReader.fillBuffer()
|
|
|
|
while not videoReader.videoEnded():
|
|
frameCount, frame = videoReader.pop()
|
|
if frameCount % (60*30) == 0:
|
|
print("Minutes processed: ", frameCount/(60*30))
|
|
|
|
if frame is None:
|
|
print("ContourExtractor: frame was None")
|
|
continue
|
|
|
|
# resize the frame, convert it to grayscale, and blur it
|
|
frame = imutils.resize(frame, width=resizeWidth)
|
|
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
|
|
|
|
# if the first frame is None, initialize it
|
|
if firstFrame is None:
|
|
#gray = np.asarray(gray[:,:,1]/2 + gray[:,:,2]/2).astype(np.uint8)
|
|
gray = cv2.GaussianBlur(gray, (5, 5), 0)
|
|
firstFrame = gray
|
|
continue
|
|
x = self.getContours(gray, firstFrame)
|
|
if x is not None:
|
|
extractedContours[frameCount] = x
|
|
|
|
print("done")
|
|
videoReader.thread.join()
|
|
self.extractedContours = extractedContours
|
|
return extractedContours
|
|
|
|
def getContours(self, gray, firstFrame):
|
|
|
|
gray = cv2.GaussianBlur(gray, (5, 5), 0)
|
|
frameDelta = cv2.absdiff(gray, firstFrame)
|
|
thresh = cv2.threshold(frameDelta, self.threashold, 255, cv2.THRESH_BINARY)[1]
|
|
# dilate the thresholded image to fill in holes, then find contours
|
|
thresh = cv2.dilate(thresh, None, iterations=3)
|
|
cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
cnts = imutils.grab_contours(cnts)
|
|
|
|
contours = []
|
|
for c in cnts:
|
|
ca = cv2.contourArea(c)
|
|
if ca < self.min_area or ca > self.max_area:
|
|
continue
|
|
(x, y, w, h) = cv2.boundingRect(c)
|
|
#print((x, y, w, h))
|
|
contours.append((x, y, w, h))
|
|
|
|
if len(contours) != 0 and contours is not None:
|
|
return contours
|
|
|
|
|
|
def displayContours(self):
|
|
values = self.extractedContours.values()
|
|
for xx in values:
|
|
for v1 in xx:
|
|
(x, y, w, h) = v1[1]
|
|
v = v1[0]
|
|
frame = np.zeros(shape=[self.yDim, self.xDim, 3], dtype=np.uint8)
|
|
frame = imutils.resize(frame, width=512)
|
|
frame[y:y+v.shape[0], x:x+v.shape[1]] = v
|
|
cv2.imshow("changes overlayed", frame)
|
|
cv2.waitKey(10) & 0XFF
|
|
cv2.destroyAllWindows()
|
|
|
|
def exportContours(self):
|
|
values = self.extractedContours.values()
|
|
frames = []
|
|
for xx in values:
|
|
for v1 in xx:
|
|
(x, y, w, h) = v1[1]
|
|
v = v1[0]
|
|
frame = np.zeros(shape=[self.yDim, self.xDim, 3], dtype=np.uint8)
|
|
frame = imutils.resize(frame, width=512)
|
|
frame[y:y+v.shape[0], x:x+v.shape[1]] = v
|
|
frames.append(frame)
|
|
return frames
|
|
|