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person_detector.py
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person_detector.py
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from __future__ import print_function
from imutils.video.pivideostream import PiVideoStream
import imutils
import time
import numpy as np
import cv2
import os
import sys
import requests
try:
SLACK_URL = os.environ['SLACK_URL']
SLACK_TOKEN = os.environ['SLACK_TOKEN']
SLACK_CHANNEL = os.environ['SLACK_CHANNEL']
except KeyError as e:
sys.exit('Couldn\'t find env: {}'.format(e))
net = cv2.dnn.readNetFromCaffe('/home/pi/models/MobileNetSSD_deploy.prototxt',
'/home/pi/models/MobileNetSSD_deploy.caffemodel')
def upload():
image = { 'file': open('hello.jpg', 'rb') }
payload = {
'filename': 'hello.jpg',
'token': SLACK_TOKEN,
'channels': [SLACK_CHANNEL],
}
requests.post(SLACK_URL, params=payload, files=image)
class PersonDetector(object):
def __init__(self, flip = True):
self.last_upload = time.time()
self.vs = PiVideoStream(resolution=(800, 608)).start()
self.flip = flip
time.sleep(2.0)
def __del__(self):
self.vs.stop()
def flip_if_needed(self, frame):
if self.flip:
return np.flip(frame, 0)
return frame
def get_frame(self):
frame = self.flip_if_needed(self.vs.read())
frame = self.process_image(frame)
ret, jpeg = cv2.imencode('.jpg', frame)
return jpeg.tobytes()
def process_image(self, frame):
frame = imutils.resize(frame, width=300)
(h, w) = frame.shape[:2]
blob = cv2.dnn.blobFromImage(frame, 0.007843, (300, 300), 127.5)
net.setInput(blob)
detections = net.forward()
count = 0
for i in np.arange(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence < 0.2:
continue
idx = int(detections[0, 0, i, 1])
if idx != 15:
continue
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype('int')
label = '{}: {:.2f}%'.format('Person', confidence * 100)
cv2.rectangle(frame, (startX, startY), (endX, endY), (0, 255, 0), 2)
y = startY - 15 if startY - 15 > 15 else startY + 15
cv2.putText(frame, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)
count += 1
if count > 0:
print('Count: {}'.format(count))
elapsed = time.time() - self.last_upload
if elapsed > 60:
cv2.imwrite('hello.jpg', frame)
upload()
self.last_upload = time.time()
return frame