TensorFlow Object Detection API

About TensorFlow Object Detection APIs

It is no doubt that machine learning and artificial intelligence are slowly taking over how we do things. From the transport industry to health and research, machine learning has become a core aspect. The introduction of driverless vehicles and robust facial detection systems require the need for object detection. Object detection APIs use computer vision to recognize the various objects found within an image or video.

What is TensorFlow Object Detection API?

Tensorflow is a software developed by Google to assist in the numerical computation of extensive machine learning programming data. Tensorflow is instrumental in object detection and hence the need to build Tensorflow vision API. A Tensorflow object detection API is a library of documentation that build computer interfaces for object recognition in videos and images.

How TensorFlow object detection APIs works

You must have a computer with a CUDA-enables graphic processing unit and a Python-based text editor to get started. Anaconda with Python version 3.7 is highly recommended. Ensure that you have installed the Tensorflow application.

The object detection APIs use Protobuf compiler to configure and train models. The TFRecord format is used in inputting data into the API. TFRecord is just an easy way of storing binary records in sequential order.

Coding for training your models is done in Python programming language. The responses to the calls made for identification return in the XML or JSON data format, depending on your selection. Thus when using the API to detect objects in an image or video, the API examines the different things in the picture. The API then returns a description of the other items based on its database of models and training.

Users

• Surveillance Companies - Companies in the security industry use the APIs for facial recognition.
• Sports Industry - In the sporting arena, the APIs are used to detect the ball in matches.
• Driverless Car Manufacturers - The driverless vehicles use the API to detect objects on the road and traffic lights.
• Gaming Industry - Computer game manufacturers use APIs when avoiding hurdles and objects.
• Medical Equipment Manufacturers - In the medical world, APIs are useful in X-Ray and MRI imaging.

Importance

• Provides real-time tracking of objects
• Scalability due to easy integration of additional functions in the future
• High accuracy in recognition and detection of objects.
• Produce detailed and insightful graphs for data analysis
• Ability to train models for your customizations.

Expectations

Tensorflow vision API is in its growth process, and with the unlimited uses at its disposal, the API is here to stay. With enhanced improvement, object detection processes, and system integrations with other platforms will be made seamless and much easier.

The API has numerous public models that you can integrate into your projects. APIs such as Google AI Vision, Object Detection, and Deepmind occur as freemiums. The free API in the category is AWSRekognition.

Best TensorFlow Object Detection APIs

1. Deep Image Object Recognition
2. Object Detection
3. Google AI Vision
4. DeepMind

TensorFlow Object Detection API SDKs

All TensorFlow Object Detection APIs are supported and made available in multiple developer programming languages and SDKs including:

1. Node.js
2. PHP
3. Python
4. Ruby
5. Objective-C
6. Java (Android)
7. C# (.NET)
8. cURL

Just select your preference from any API endpoints page.

Sign up today for free on RapidAPI to begin using TensorFlow Object Detection APIs!