One of the important fields of Artificial Intelligence is the computer vision. Computer vision is the science of computers and related software systems which can recognize the objects and scenes. It deals with various aspects such as object detection, image recognition, image generation and many more. Likewise, there are several amazing uses of object detection which will definitely come from the efforts of computer programmers and software developers.
The adoption of deep learning techniques helps to use accurate object detection algorithms and methods.
Now let’s walk through the concept i.e what is object detection with respect to AI.
What is object detection in a video file with respect to AI?
Object detection is a branch of computer vision used to observe objects as the images in the videos which can be located, detected and recognized by the computers. In this 21st century, detecting of images and objects in a video has become quite possible with the help of deep learning algorithms. There are specialized algorithms which are developed for detecting, locating and recognizing the objects in videos. The most beneficial algorithm is the SSD – Single Shot Detection and RetinaNet etc.
To be more concise, if you want to apply AI based deep learning techniques to detect and recognize the objects, it requires huge computational power systems, applied mathematics and solid technical knowledge with thousands of line of code.
With the help of IBM Watson AI services, you can generate accurate results in less turnaround time. With the help of IBM AI services, you can get qualitative solutions where both human intelligence and machine intelligence are clubbed together.
IBM Watson provides a flexible environment for deploying AI applications. You can use those tools, volumes of data so as to attain a very good throughput and GPU acceleration. In order to develop new object detection, applications require more computational power beyond the CPUs. We need GPUs which provide the best accuracy in less time. Here’s what the Watson AI does, it comes with best GPU power.
Writing deep learning and neural networks code from scratch is not easy for any developer, it requires a combination of human and machine intelligence. Keeping that in consideration IBM Watson provides all the frameworks and models required which are the reusable components.
Yes, here I am going to discuss the algorithm Single Shot Detection(SSD) which helps in object detection.
Single Shot Detection Algorithm
The SSD algorithm is one of the topmost algorithms to detect objects. It uses the multi-box concept, predicting object positions and scale problem.
So, how do the computers or object detection algorithms detect the objects?
If you use the algorithms to scale the solution you need to train the algorithm and that is difficult. So by using the SSD concept i.e multi-box detection, we are segmenting the image into several segments and then construct boxes for every segment.
Real Time Object Detection With Deep Learning:
The deep learning and neural networks are the most powerful methods with respect to computers vision as computer will have the brain to do detections.
Now I am going to detect an object inside an video.
Before proceeding further don’t forget to connect to the virtual platform where your code is processed for output.
As a next step you need to import all the classes defined into your virtual environment.
You need to exact your folder into your virtual platform. It contains the data folder which handles the transformations required for the input images in the video.
I had created a filename with the following name.
File name: voc0712.py
***VOC Dataset Classes*****
‘Returns the original image object at index in PIL form
Note: not using self.__getitem__(), as any transformations passed in
could mess up this functionality.
Another folder layer which is used for some detections such as multi box detection with respect to SSD algorithm. Now you need to import the libraries required.
After preparing the datasets and layers for manipulation you need to proceed to the actual coding part where you will be going to do some detections on the video.
Code for Object Detection based on IBM AI deep learning techniques:
Step1: You need to open up a new file and name it as real time object detection, after naming import the libraries required.
Step2: You should define the functions that will perform detections.
# Defining a function that will do the detections
def detect(frame, net, transform): # We define a detect function that will take as inputs, a frame, a ssd neural network, and a transformation to be applied on the images, and that will return the frame with the detector rectangle.
Step 3: You need to create the SSD neural network as follows.
# Creating the SSD neural network
Step 4: Now it’s the time create the transformations.
# Creating the transformation
Step 5: Now with the follow code you can do some object detection on a video.
# Doing some Object Detection on a video
Step 6: Close the file which handles detections.
With the following code you can definitely achieve your target to detect the objects in the video. However with the help of the SSD algorithm we did a great job to do detections. IBM AI services also helped the developers do similar tasks to identify or detect any objects in a video with their secured and encrypted platform. Now it’s the time to deploy your code with the IBM AI cloud to generate qualitative and accurate results.