app.py
import json
import os
import time
import numpy as np
import requests
import objtracker
from exts import passers_by_requests_post, video_post, data_post, capture_path
from objdetector import Detector
from objdetector_car import Detector as CarDetector
import cv2
from pydub import AudioSegment
from pydub.playback import play
from flask import Flask, Response, request
from urls import host_ip
import _thread
app = Flask(__name__)
def run(VIDEO_PATH, data_post_url, data_dict, label):
# 根据视频尺寸，填充供撞线计算使用的polygon
width = 1920
height = 1080
mask_image_temp = np.zeros((height, width), dtype=np.uint8)
# 用于记录轨迹信息
pts = {}
# 填充第一个撞线polygon（蓝色）
list_pts_blue = [[204, 305], [227, 431], [605, 522], [1101, 464], [1900, 601], [1902, 495], [1125, 379], [604, 437],
[299, 375], [267, 289]]
ndarray_pts_blue = np.array(list_pts_blue, np.int32)
polygon_blue_value_1 = cv2.fillPoly(mask_image_temp, [ndarray_pts_blue], color=1)
polygon_blue_value_1 = polygon_blue_value_1[:, :, np.newaxis]
# 填充第二个撞线polygon（黄色）
mask_image_temp = np.zeros((height, width), dtype=np.uint8)
list_pts_yellow = [[181, 305], [207, 442], [603, 544], [1107, 485], [1898, 625], [1893, 701], [1101, 568],
[594, 637], [118, 483], [109, 303]]
ndarray_pts_yellow = np.array(list_pts_yellow, np.int32)
polygon_yellow_value_2 = cv2.fillPoly(mask_image_temp, [ndarray_pts_yellow], color=2)
polygon_yellow_value_2 = polygon_yellow_value_2[:, :, np.newaxis]
# 撞线检测用的mask，包含2个polygon，（值范围 0、1、2），供撞线计算使用
polygon_mask_blue_and_yellow = polygon_blue_value_1 + polygon_yellow_value_2
# 缩小尺寸，1920x1080->960x540
polygon_mask_blue_and_yellow = cv2.resize(polygon_mask_blue_and_yellow, (width // 2, height // 2))
# 蓝 色盘 b,g,r
blue_color_plate = [255, 0, 0]
# 蓝 polygon图片
blue_image = np.array(polygon_blue_value_1 * blue_color_plate, np.uint8)
# 黄 色盘
yellow_color_plate = [0, 255, 255]
# 黄 polygon图片
yellow_image = np.array(polygon_yellow_value_2 * yellow_color_plate, np.uint8)
# 彩色图片（值范围 0-255）
color_polygons_image = blue_image + yellow_image
# 缩小尺寸，1920x1080->960x540
color_polygons_image = cv2.resize(color_polygons_image, (width // 2, height // 2))
# list 与蓝色polygon重叠
list_overlapping_blue_polygon = []
# list 与黄色polygon重叠
list_overlapping_yellow_polygon = []
# 下行数量
down_count = 0
# 上行数量
up_count = 0
font_draw_number = cv2.FONT_HERSHEY_SIMPLEX
draw_text_postion = (int((width / 2) * 0.01), int((height / 2) * 0.05))
# 实例化yolov5检测器
if label == "person":
detector = Detector()
elif label == "car":
detector = CarDetector()
# 打开视频
capture = cv2.VideoCapture(VIDEO_PATH)
# song = AudioSegment.from_wav("程序已经启动.wav")
# play(song)
# os.system("mpg123 程序已经启动.mp3")
# try:
# _thread.start_new_thread(os.system, ("mpg123 程序已经启动.mp3",))
# except:
# print("Error: 无法启动线程")
# speak_old_time = time.time()
old_time = time.time()
while True:
# 读取每帧图片
_, im = capture.read()
if im is None:
break
# 缩小尺寸，1920x1080->960x540
im = cv2.resize(im, (width // 2, height // 2))
list_bboxs = []
# 更新跟踪器
output_image_frame, list_bboxs = objtracker.update(detector, im)
source_output_image_frame = output_image_frame
# print(list_bboxs)
# 输出图片
output_image_frame = cv2.add(output_image_frame, color_polygons_image)
if len(list_bboxs) > 0:
# ----------------------判断撞线----------------------
for item_bbox in list_bboxs:
# print(item_bbox)
x1, y1, x2, y2, _, track_id = item_bbox
# 撞线检测点，(x1，y1)，y方向偏移比例 0.0~1.0
y1_offset = int(y1 + ((y2 - y1) * 0.5))
x1_offset = int(x1 + ((x2 - x1) * 0.5))
# 撞线的点
y = y1_offset
x = x1_offset
# 然后每检测出一个预测框，就将中心点加入队列
center = (x, y)
if track_id in pts:
pts[track_id].append(center)
else:
pts[track_id] = []
pts[track_id].append(center)
thickness = 2
cv2.circle(output_image_frame, (center), 1, [255, 255, 255], thickness)
for j in range(1, len(pts[track_id])):
if pts[track_id][j - 1] is None or pts[track_id][j] is None:
continue
cv2.line(output_image_frame, (pts[track_id][j - 1]), (pts[track_id][j]), [255, 255, 255], thickness)
if polygon_mask_blue_and_yellow[y, x] == 1:
# 如果撞 蓝polygon
if track_id not in list_overlapping_blue_polygon:
list_overlapping_blue_polygon.append(track_id)
# 判断 黄polygon list里是否有此 track_id
# 有此track_id，则认为是 UP (上行)方向
if track_id in list_overlapping_yellow_polygon:
# 上行+1
up_count += 1
# TODO print('up count:', up_count, ', up id:', list_overlapping_yellow_polygon)
print('up count:', up_count, ', up id:', list_overlapping_yellow_polygon)
# try:
# passers_by_requests_post({
# 'up_or_down': 'up',
# 'count': down_count,
# 'id': list_overlapping_blue_polygon
# })
# except:
# print("无法连接到服务器")
# 删除 黄polygon list 中的此id
list_overlapping_yellow_polygon.remove(track_id)
elif polygon_mask_blue_and_yellow[y, x] == 2:
# 如果撞 黄polygon
if track_id not in list_overlapping_yellow_polygon:
list_overlapping_yellow_polygon.append(track_id)
# 判断 蓝polygon list 里是否有此 track_id
# 有此 track_id，则 认为是 DOWN（下行）方向
if track_id in list_overlapping_blue_polygon:
# 下行+1
down_count += 1
# TODO print('down count:', down_count, ', down id:', list_overlapping_blue_polygon)
print('down count:', down_count, ', down id:', list_overlapping_blue_polygon)
# try:
# passers_by_requests_post({
# 'up_or_down': 'down',
# 'count': down_count,
# 'id': list_overlapping_blue_polygon
# })
# except:
# print("无法连接到服务器")
# 删除 蓝polygon list 中的此id
list_overlapping_blue_polygon.remove(track_id)
# ----------------------清除无用id----------------------
list_overlapping_all = list_overlapping_yellow_polygon + list_overlapping_blue_polygon
for id1 in list_overlapping_all:
is_found = False
for _, _, _, _, _, bbox_id in list_bboxs:
if bbox_id == id1:
is_found = True
if not is_found:
# 如果没找到，删除id
if id1 in list_overlapping_yellow_polygon:
list_overlapping_yellow_polygon.remove(id1)
if id1 in list_overlapping_blue_polygon:
list_overlapping_blue_polygon.remove(id1)
list_overlapping_all.clear()
# 清空list
list_bboxs.clear()
else:
# 如果图像中没有任何的bbox，则清空list
list_overlapping_blue_polygon.clear()
list_overlapping_yellow_polygon.clear()
# 输出计数信息
text_draw = 'lane one: ' + str(down_count) + \
' , lane two: ' + str(up_count)
source_output_image_frame = cv2.putText(img=source_output_image_frame, text=text_draw,
org=draw_text_postion,
fontFace=font_draw_number,
fontScale=0.75, color=(0, 0, 255), thickness=2)
output_image_frame = cv2.putText(img=output_image_frame, text=text_draw,
org=draw_text_postion,
fontFace=font_draw_number,
fontScale=0.75, color=(0, 0, 255), thickness=2)
# TODO send data
res_dict = {"down_count": down_count, "up_count": up_count}
print("send data:", res_dict)
# data_post(res_dict, data_post_url)
# 创建线程
try:
_thread.start_new_thread(data_post, (res_dict, data_post_url,))
except:
print("Error: 无法启动线程")
# cv2.imshow('Counting Demo', output_image_frame)
# cv2.waitKey(1)
# TODO 上传图片到服务器
if time.time() - old_time > 5:
old_time = time.time()
img_path = os.path.join(os.getcwd(), "results", "result.png")
print('img_path:', img_path)
cv2.imwrite(img_path, output_image_frame)
files = {'file': open(img_path, 'rb')}
# 创建线程
try:
_thread.start_new_thread(video_post, (files, data_dict,))
except:
print("Error: 无法启动线程")
cv2.imshow("f", source_output_image_frame)
cv2.waitKey(1)
# TODO stream results
ret, jpeg = cv2.imencode('.jpg', source_output_image_frame)
frame = jpeg.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
# if time.time() - old_time > 10:
# old_time = time.time()
# img_path = os.path.join(os.getcwd(), "result.png")
# # cv2.imwrite(img_path, cv2.resize(output_image_frame, (160, 160)))
# cv2.imwrite(img_path, output_image_frame)
# files = {'file': open(img_path, 'rb')}
# try:
# status_ = video_post(files)
# # print(status_)
# except:
# print('无法连接到服务器')
capture.release()
cv2.destroyAllWindows()
@app.route("/")
def person():
source_ = request.args.get("source")
# realtime = request.args.get("realtime")
if source_ is not None:
source = source_
else:
source = "video/test_person.mp4"
opt_dict = {
"VIDEO_PATH": source,
"data_post_url": "/api/passers_by/set_data",
'data_dict': {"pic_type": 'deepsort_person'},
'label': "person"
}
return Response(run(**opt_dict), mimetype='multipart/x-mixed-replace; boundary=frame')
@app.route("/car")
def car():
realtime = request.args.get("realtime")
if realtime == "true":
source = capture_path()
else:
source = "video/test_traffic.mp4"
opt_dict = {
"VIDEO_PATH": source,
"data_post_url": "/api/car/set_data",
'data_dict': {"pic_type": 'deepsort_car'},
'label': "car"
}
return Response(run(**opt_dict), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == "__main__":
app.run(
port=5002,
host='0.0.0.0'
)
# with open('../../configs.json', 'r') as f:
# configs = json.load(f)
#
# if configs["function"]["5002"] is True:
# app.run(
# port=5002,
# host='0.0.0.0'
# )
# else:
# print("请在配置文件中开启该功能 !!")