An iOS app for object detection server/client model

by iOS Example

iOS Object Detection App

This is a client app which means you are going to need a server in order to run the application. A server with a powerful GPU and high network bandwidth is recommanded.

Requirements

  • BlueSocket (within the project file)
  • Xcode 8
  • iOS 10
  • Server

SOIC

​ Self-Organizing Incremental Neural Network with Convolution. Enable life-long image recognition. Details omited.

YOLOv2

  • iOS -> Select/Take Image -> Compress Image -> Send to server -> Receive Image -> Display -> (Optional) Feedback to server
  • Voice recognition
  • A very naive sentimental anaysis for rating(feedback).
  • ​Real-time object detection is not supported due to the limitation of the network bandwidth(sending image to server, though compressed, is still time consuming).

Server

​ Server should listen imcomming TCP connections on both port 23333 and 23334(Optional), port 23333 is used to receive/send images. Server example:

def run(self):
    self.log.write("iOS server starts, listenning for connections...")
    while self.keep_running:
      self.listen() # listen for connections on port 23333
      self.recv_img() # receive image from port 23333
      self.detect_img() # do object detection (faster-rnn, yolo, etc.)
      self.sent_img() # send processed image back to client on port 23333

​ An example server file named ios_server_exmaple is provided, which is implemented in python3 with YOLOv2(search darkflow in github) to do object detection.

Test

​ This app has been tested on iPhone7 plus with latest iOS version(10.3). For any questions feel free to ask by sending email to adamzjk@foxmail.com or submit an issue!

GitHub