import sys

import numpy as np

import cv2

from os import system

import io, time

from os.path import isfile, join

import re

import picamera

from imutils.video.pivideostream import PiVideoStream

from imutils.video import FPS

from picamera.array import PiRGBArray

from picamera import PiCamera

import imutils

fps = ""

detectfps = ""

framecount = 0

detectframecount = 0

time1 = 0

time2 = 0

LABELS = ('background',

'sheep', 'sofa', 'train', 'tvmonitor')

camera_width = 640

camera_height = 480

net = cv2.dnn.readNet('caffemodel/MobileNetSSD/MobileNetSSD_deploy.caffemodel', 'caffemodel/MobileNetSSD/MobileNetSSD_deploy.prototxt')

net.setPreferableTarget(cv2.dnn.DNN_TARGET_MYRIAD)

net.setPreferableBackend(cv2.dnn.DNN_BACKEND_INFERENCE_ENGINE)

try:

vs = PiVideoStream((camera_width, camera_height)).start()

time.sleep(2)

while True:

t1 = time.perf_counter()

color_image = vs.read()

height = color_image.shape[0]

width = color_image.shape[1]

blob = cv2.dnn.blobFromImage(color_image, size=(300, 300), ddepth=cv2.CV_8U, swapRB=False, crop=False)

net.setInput(blob, scalefactor=1.0/127.5, mean=[127.5, 127.5, 127.5])

out = net.forward()

out = out.flatten()

for box_index in range(100):

if out[box_index + 1] == 0.0:

break

base_index = box_index * 7

if (not np.isfinite(out[base_index]) or

not np.isfinite(out[base_index + 1]) or

not np.isfinite(out[base_index + 2]) or

not np.isfinite(out[base_index + 3]) or

not np.isfinite(out[base_index + 4]) or

not np.isfinite(out[base_index + 5]) or

not np.isfinite(out[base_index + 6])):

continue

if box_index == 0:

detectframecount += 1

x1 = max(0, int(out[base_index + 3] * height))

y1 = max(0, int(out[base_index + 4] * width))

x2 = min(height, int(out[base_index + 5] * height))

y2 = min(width, int(out[base_index + 6] * width))

object_info_overlay = out[base_index:base_index + 7]

min_score_percent = 60

source_image_width = width

source_image_height = height

base_index = 0

class_id = object_info_overlay[base_index + 1]

percentage = int(object_info_overlay[base_index + 2] * 100)

if (percentage <= min_score_percent):

continue

box_left = int(object_info_overlay[base_index + 3] * source_image_width)

box_top = int(object_info_overlay[base_index + 4] * source_image_height)

box_right = int(object_info_overlay[base_index + 5] * source_image_width)

box_bottom = int(object_info_overlay[base_index + 6] * source_image_height)

label_text = LABELS[int(class_id)] + " (" + str(percentage) + "%)"

box_color = (255, 128, 0)

box_thickness = 1

cv2.rectangle(color_image, (box_left, box_top), (box_right, box_bottom), box_color, box_thickness)

label_background_color = (125, 175, 75)

label_text_color = (255, 255, 255)

label_size = cv2.getTextSize(label_text, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)[0]

label_left = box_left

label_top = box_top - label_size[1]

if (label_top < 1):

label_top = 1

label_right = label_left + label_size[0]

label_bottom = label_top + label_size[1]

cv2.rectangle(color_image, (label_left - 1, label_top - 1), (label_right + 1, label_bottom + 1), label_background_color, -1)

cv2.putText(color_image, label_text, (label_left, label_bottom), cv2.FONT_HERSHEY_SIMPLEX, 0.5, label_text_color, 1)

cv2.putText(color_image, fps, (width-170,15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (38,0,255), 1, cv2.LINE_AA)

cv2.putText(color_image, detectfps, (width-170,30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (38,0,255), 1, cv2.LINE_AA)

cv2.namedWindow('Pi Camera', cv2.WINDOW_AUTOSIZE)

cv2.imshow('Pi Camera', cv2.resize(color_image, (width, height)))

if cv2.waitKey(1)&0xFF == ord('q'):

break

# FPS calculation

framecount += 1

if framecount >= 15:

fps = "(Playback) {:.1f} FPS".format(time1/15)

detectfps = "(Detection) {:.1f} FPS".format(detectframecount/time2)

framecount = 0

detectframecount = 0

time1 = 0

time2 = 0

t2 = time.perf_counter()

elapsedTime = t2-t1

time1 += 1/elapsedTime

time2 += elapsedTime

except:

import traceback

traceback.print_exc()

finally:

vs.stop()

print("\n\nFinished\n\n")