class VideoFileCamera(Thread):
def __init__(self, video_file, queue):
super().__init__()
self.queue = queue
self.video_file = video_file
self.THRESHOLD = 0.25
self.detecter = Detecter()
def run(self):
cap = cv2.VideoCapture(self.video_file)
fps = cap.get(cv2.CAP_PROP_FPS)
delay = int(1000/fps)
# detecter = Detecter()
self.detecter.setup('./frozen_inference_graph.pb', './mscoco_label_map.pbtxt')
while(cap.isOpened()):
_, frame = cap.read()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# frame_ex = np.expand_dims(frame, axis=0)
# (boxes, scores, classes, num) = self.detecter.detect(frame_ex)
# self.detecter.viaulize(frame, boxes, classes, scores, self.THRESHOLD)
self.queue.put(frame, timeout=2)
cv2.waitKey(delay)
cap.release()
cv2.destroyAllWindows()
def __init__(self, name, queue):
super().__init__()
self.name = name
self.queue = queue
self.THRESHOLD = 0.25
self.detecter = Detecter()
self.detecter.setup('./frozen_inference_graph.pb',
'./mscoco_label_map.pbtxt')
pass
class Objectdetecter:
def __init__(self):
self.detecter = Detecter()
self.detecter.setup(
'./data/ssd_mobilenet_v1/frozen_inference_graph.pb',
'./data/label_map.pbtxt')
self.THRESHOLD = 0.8
def __check(self, image):
detect_image = np.copy(image)
image = np.expand_dims(image, axis=0)
(boxes, scores, classes, num) = self.detecter.detect(image)
list = []
self.detecter.viaulize(detect_image, boxes, classes, scores,
self.THRESHOLD)
for output in zip(classes, scores, boxes):
if output[1] >= self.THRESHOLD:
y1, x1, y2, x2 = output[2]
y = int((y2 - y1) * 480)
list.append((output, y))
return list, detect_image
def order(self, image):
lists, detect_image = self.__check(image)
sign = 5
tra = 5
st = 300
fw = 5
for list in lists:
if list[0][0] == 5:
c = list[1]
if c > sign:
return 'stopsign', detect_image
elif list[0][0] == 6:
c = list[1]
if c > tra:
return 'trash', detect_image
elif list[0][0] == 1:
c = list[1]
if c < st:
return 'stop', detect_image
elif list[0][0] == 2:
c = list[1]
if c > fw:
return 'forward', detect_image
return None, detect_image
def job():
stack=[]
PATH="data/images/"
date=datetime.datetime.now().strftime("%Y-%m-%d")
target =date+".mp4"
os.mkdir(PATH+date)
cam = cv2.VideoCapture("data/videos/" + target)
minute=datetime.datetime.now().minute
FPS = 1
try:
if not os.path.exists('data'):
os.makedirs('data')
except OSError:
print('Error: Creating directory of data')
currentframe = 0
capture_rate = 60#int(cam.get(cv2.CAP_PROP_FPS))
end_of_frame = cam.get(cv2.CAP_PROP_FRAME_COUNT)
# print(end_of_frame)
stat_of_frame =0# minute*(cam.get(cv2.CAP_PROP_FPS) * 60)
# print(stat_of_frame)
for i in range(TOTAL_MIN//SAMPLING_CYCLE):
for j in range(SAMPLING_CYCLE):
cam.set(cv2.CAP_PROP_POS_FRAMES, CAPTURE_CYCLE * (currentframe*FPS) + stat_of_frame)
ret, frame = cam.read()
if ret:
# if currentframe % capture_rate == 0:
name = 'data/frames/frame' + str(j) + '.jpg'
cv2.imwrite(name, frame)
if j == 0:
# print(PATH+date+'/'+str(i))
cv2.imwrite(PATH+date+'/'+str(i)+'.jpg', frame)
else:
break
currentframe += 1
result = Detecter.detect()
output=round(result/CAPTURE_CYCLE,2)
# print(datetime.datetime.now().strftime("%Y-%m-%d"),i,": Avg =",output)
stack.append(output)
plt.plot(range(TOTAL_MIN//SAMPLING_CYCLE),stack)
plt.savefig(target+'result.png')
mosaicer.process(PATH+date+'/')
cam.release()
cv2.destroyAllWindows()
class ImageViewer(Thread):
def __init__(self, name, queue):
super().__init__()
self.name = name
self.queue = queue
self.THRESHOLD = 0.25
self.detecter = Detecter()
self.detecter.setup('./frozen_inference_graph.pb',
'./mscoco_label_map.pbtxt')
pass
def run(self):
while (True):
frame = self.queue.get(timeout=2)
frame_ex = np.expand_dims(frame, axis=0)
(boxes, scores, classes, num) = self.detecter.detect(frame_ex)
self.detecter.viaulize(frame, boxes, classes, scores,
self.THRESHOLD)
cv2.imshow(self.name, frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
pass
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
image_ex = np.expand_dims(frame, axis=0)
(boxes, scores, classes, num) = detecter.detect(image_ex)
detecter.viaulize(frame, boxes, classes, scores, THRESHOLD)
cv2.imshow('people', frame)
def play1():
print(path)
cap = cv2.VideoCapture(path)
while(cap.isOpened()):
ret, frame = cap.read()
detect1(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
detecter = Detecter()
detecter.setup('./frozen_inference_graph.pb','./mscoco_label_map.pbtxt')
THRESHOLD = 0.3
path = "vtest.avi"
t = Thread(target=play1, args=())
t.start()
import cv2
import numpy as np
from picamera.array import PiRGBArray
from picamera import PiCamera
from detecter import Detecter
THRESHOLD = 0.3
detecter = Detecter()
detecter.setup('./frozen_inference_graph.pb', './mscoco_label_map.pbtxt')
# 파이카메라 준비
# 카메라 해상도
IM_WIDTH = 640
IM_HEIGHT = 480
# PiCamera 설정
camera = PiCamera()
camera.resolution = (IM_WIDTH, IM_HEIGHT)
camera.framerate = 10
rawCapture = PiRGBArray(camera, size=(IM_WIDTH, IM_HEIGHT))
rawCapture.truncate(0)
for frame1 in camera.capture_continuous(rawCapture,
format="bgr",
use_video_port=True):
image = np.copy(frame1.array)
image.setflags(write=1)
image_ex = np.expand_dims(image, axis=0)
# detection
(boxes, scores, classes, num) = detecter.detect(image_ex)
def __init__(self, video_file, queue):
super().__init__()
self.queue = queue
self.video_file = video_file
self.THRESHOLD = 0.25
self.detecter = Detecter()
def __init__(self):
self.detecter = Detecter()
self.detecter.setup(
'./data/ssd_mobilenet_v1/frozen_inference_graph.pb',
'./data/label_map.pbtxt')
self.THRESHOLD = 0.8
import cv2
import os
from detecter import Detecter
from mosaicer import mosaicer
import schedule
import time
import datetime
import matplotlib.pyplot as plt
from config import SAMPLING_CYCLE,TOTAL_MIN,CAPTURE_CYCLE
Detecter = Detecter()
mosaicer = mosaicer()
def job():
stack=[]
PATH="data/images/"
date=datetime.datetime.now().strftime("%Y-%m-%d")
target =date+".mp4"
os.mkdir(PATH+date)
cam = cv2.VideoCapture("data/videos/" + target)
minute=datetime.datetime.now().minute
FPS = 1
try:
if not os.path.exists('data'):
os.makedirs('data')
except OSError:
print('Error: Creating directory of data')