Machine Learning in Brief
Machine learning is an application of Artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.
Machine Learning from Image Processing
How often you come across use cases where images need to be recognized and meaningful data is generated from these images, example it can be as simple as identifying an abnormality is growth of tissues or bones that if recognized can help in identifying and curing the disorder in early stage
Goal
the goal of this blog is to create a TensorFlow Machine Learning environment and to analyze an image rather do an image recognition
Setup ML Environment
Login to Bitnami Console and Create an Instance of TensorFlow from the following link
In this case we will select TensorFlow Serving v1.5.0.1
within few mins this should create instance on Oracle Cloud
SSH into TensorFlow Invironment
Download Public and Private Key
ssh -i bitnami-opc-a457995.pem bitnami@publicIP
Let us study this first image, let TensorFlow use its ML Algorithms to figure out which image is this
bitnami@ubuntu:/tmp$ curl -LO 'https://d1u4oo4rb13yy8.cloudfront.net/article-sddntirixr-1442081001.jpeg' % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 102k 100 102k 0 0 14735 0 0:00:07 0:00:07 --:--:-- 50014 bitnami@ubuntu:/tmp$ inception_client --image=article-sddntirixr-1442081001.jpeg outputs { key: "classes" value { dtype: DT_STRING tensor_shape { dim { size: 1 } dim { size: 5 } } string_val: "vault" string_val: "triumphal arch" string_val: "monastery" string_val: "mosque" string_val: "altar" } } outputs { key: "scores" value { dtype: DT_FLOAT tensor_shape { dim { size: 1 } dim { size: 5 } } float_val: 8.59596157074 float_val: 8.14022350311 float_val: 7.99082612991 float_val: 7.0765748024 float_val: 6.69686365128 } }
Let us use one more image to Analyze
bitnami@ubuntu:/tmp$ curl -LO 'https://spiderimg.amarujala.com/assets/images/2018/03/22/750x506/brahmos_1521703360.jpeg' % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 68380 100 68380 0 0 13513 0 0:00:05 0:00:05 --:--:-- 1804k bitnami@ubuntu:/tmp$ inception_client --image=brahmos_1521703360.jpeg outputs { key: "classes" value { dtype: DT_STRING tensor_shape { dim { size: 1 } dim { size: 5 } } string_val: "missile" string_val: "projectile, missile" string_val: "airliner" string_val: "warplane, military plane" string_val: "wing" } } outputs { key: "scores" value { dtype: DT_FLOAT tensor_shape { dim { size: 1 } dim { size: 5 } } float_val: 9.67117881775 float_val: 9.28978347778 float_val: 7.33030891418 float_val: 5.74678897858 float_val: 4.2038693428 } } bitnami@ubuntu:/tmp$
Blog Author
Madhusudhan Rao