Food Image Classification - Build An Image Classifier with IBM Watson - Part 6

Nicholas Renotte · Intermediate ·👁️ Computer Vision ·7y ago

Key Takeaways

This video demonstrates how to build an image classifier using IBM Watson's Visual Recognition service, specifically utilizing the food classifier to classify images of food. The tutorial uses Python to implement the classifier and provides a step-by-step guide on how to use the custom classifiers provided by IBM Watson.

Full Transcript

so welcome to step 6 of our mini-series on building your own image recognition classifier so what we've done in the last step is gone through some general image recognition but now what we can do is start using some of the custom classifiers that IBM's got built in to the visual recognition service now this is actually a reasonably easy step to step over in sight using some of these custom classifiers so and one of the ones that we're going to use is the food classifier so the food classifier is a more specific classifier that's already built within the visual recognition service and allow them I guess delve into more detailed classifications of food so let's try this yet so so before we were using an image of a computer on our image class by 7 let's try an image of an orange for example and let's grab yeah this one should do let's check it's fine again yeah that should be fine so again to make sure it's still a JPEG file and what we'll do now is we'll replace this URL with our URL of our orange and now we're going to add in an extra parameter into this classifier method so we're still classifying at the moment what we're going to do now is we're going to extend or delve into some of the more custom classifiers that IBM's got there and to do this all we need to do is type in classifier always type this wrong and IDs equals food so now this will allow us to tap into that so let's try this and we should actually see here if everything's run successfully this classifier D translates or changes to food so let's try running that cell again so it looks like it's run successfully and you can see that now that it's actually picked up the food classifier and again it's classified it as an orange pretty successfully now this might seem like a bit of a trivial step but it's actually pretty important because in the next video we're actually going to go through how to create your own custom classifications and you'll see there that all the customer classifications that the we generate going to show up as classifier IDs

Original Description

Tired of struggling to build an image classifier from scratch, this series goes through how to start, build and use an image classifier using IBM Watson from start to finish using Python. Need help? Check out the blog post:https://www.nicholasrenotte.com/how-to-build-your-first-image-recognition-classifier-with-ibm-watson-visual-recognition/
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Playlist

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1 Face Detection - Build An Image Classifier with IBM Watson - Part 7
Face Detection - Build An Image Classifier with IBM Watson - Part 7
Nicholas Renotte
Food Image Classification - Build An Image Classifier with IBM Watson - Part 6
Food Image Classification - Build An Image Classifier with IBM Watson - Part 6
Nicholas Renotte
3 General Image Classification - Build An Image Classifier with IBM Watson - Part 5
General Image Classification - Build An Image Classifier with IBM Watson - Part 5
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4 Installing Watson Developer Cloud - Build An Image Classifier with IBM Watson - Part 4
Installing Watson Developer Cloud - Build An Image Classifier with IBM Watson - Part 4
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5 Generating Credentials - Build An Image Classifier with IBM Watson - Part 3
Generating Credentials - Build An Image Classifier with IBM Watson - Part 3
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6 Creating A Service - Build An Image Classifier with IBM Watson - Part 2
Creating A Service - Build An Image Classifier with IBM Watson - Part 2
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7 Getting an IBMid - Build An Image Classifier with IBM Watson - Part 1
Getting an IBMid - Build An Image Classifier with IBM Watson - Part 1
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8 How to Analyse Review Data - Part 2 - Python Yelp Sentiment Analysis
How to Analyse Review Data - Part 2 - Python Yelp Sentiment Analysis
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9 How to Lemmatize Text - Part 4 - Python Yelp Sentiment Analysis
How to Lemmatize Text - Part 4 - Python Yelp Sentiment Analysis
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10 How to Calculate Sentiment Using TextBlob - Part 5 - Python Yelp Sentiment Analysis
How to Calculate Sentiment Using TextBlob - Part 5 - Python Yelp Sentiment Analysis
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11 How to Collect Business Reviews Using Python - Part 1 - Python Yelp Sentiment Analysis
How to Collect Business Reviews Using Python - Part 1 - Python Yelp Sentiment Analysis
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12 How to Clean Text Based Data for NLP - Part 3 - Python Yelp Sentiment Analysis
How to Clean Text Based Data for NLP - Part 3 - Python Yelp Sentiment Analysis
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13 How to Setup a IBM Watson Personality Insights Service - Part 1 - Watson Personality Insights
How to Setup a IBM Watson Personality Insights Service - Part 1 - Watson Personality Insights
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14 How to Create a Customer Profile with IBM Watson - Part 2 - Watson Personality Insights
How to Create a Customer Profile with IBM Watson - Part 2 - Watson Personality Insights
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15 Visualising The Profile   Part 3   Watson Personality Insights
Visualising The Profile Part 3 Watson Personality Insights
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16 How to Plot Personality Insights Features at Lightspeed - Part 4  - IBM Watson Personality Insights
How to Plot Personality Insights Features at Lightspeed - Part 4 - IBM Watson Personality Insights
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17 Getting Started With IBM Watson Studio Machine Learning - Part 1 - Predicting Used Car Prices
Getting Started With IBM Watson Studio Machine Learning - Part 1 - Predicting Used Car Prices
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18 Upload and Visualize Data In IBM Watson Studio - Part 2 - Predicting Used Car Prices
Upload and Visualize Data In IBM Watson Studio - Part 2 - Predicting Used Car Prices
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19 Clean Data and Feature Engineer in IBM Watson Studio - Part  3 - Predict Used Car Prices
Clean Data and Feature Engineer in IBM Watson Studio - Part 3 - Predict Used Car Prices
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20 Using Watson Model Builder to Predict Car Prices - Part 4 - Predicting Used Car Prices
Using Watson Model Builder to Predict Car Prices - Part 4 - Predicting Used Car Prices
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21 Deploy and Make Predictions With Watson Studio - Part 5 - Predicting Used Car Prices
Deploy and Make Predictions With Watson Studio - Part 5 - Predicting Used Car Prices
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22 Getting Started With IBM Watson Discovery - Part 1 - Stock News Crawler
Getting Started With IBM Watson Discovery - Part 1 - Stock News Crawler
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23 How to Run Advanced Queries with Watson Discovery - Part 5 - Stock News Crawler
How to Run Advanced Queries with Watson Discovery - Part 5 - Stock News Crawler
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24 How to Run Search Queries with IBM Watson Discovery - Part 4 - Stock News Crawler
How to Run Search Queries with IBM Watson Discovery - Part 4 - Stock News Crawler
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25 How to Understand the Watson Discovery Data Schema  - Part 3 - Stock News Crawler
How to Understand the Watson Discovery Data Schema - Part 3 - Stock News Crawler
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26 How to Build a Watson Discovery Web Crawler - Part 2 - Stock News Crawler
How to Build a Watson Discovery Web Crawler - Part 2 - Stock News Crawler
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27 AI learns what to do next using Tensorflow and Python
AI learns what to do next using Tensorflow and Python
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28 Chatbot Crash Course for Absolute Beginners - Full 20 Minute Tutorial
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29 Shopify Customer Service Chatbot using Python Automation
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30 Building a Reddit Keyword Research Chatbot
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31 Chatbot App Tutorial with Javascript Node.js [Part 1]
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32 Javascript Chatbot From Scratch with React.Js [Part 2]
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33 Predicting Churn with Automated Python Machine Learning
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34 Sales Forecasting in Excel with Machine Learning and Python Automation
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35 Automate Budgeting with Python and Planning Analytics
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37 Optimizing Marketing Spend using Linear Programming || Marketing Opt PT.1
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38 Solving Optimization Problems with Python Linear Programming
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39 Loading Data into Planning Analytics with Python || Marketing Opt PT.2
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40 Building Marketing Dashboards with Planning Analytics Workspace || Marketing Opt PT.3
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41 Optimizing Resource Allocation with Docplex and Planning Analytics || Marketing Opt PT.4
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42 Exploratory Data Analysis With Pandas || Python Machine Learning PT.1
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43 Preparing Pandas Dataframes for Machine Learning || Python Machine Learning PT.2
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44 Python Machine Learning with Scikit Learn - Regression || Python Machine Learning PT.3
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45 Deploying Machine Learning Models with Watson Machine Learning || Python Machine Learning PT.4
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46 Mind Blowing Machine Learning Apps with Node.JS and Watson Machine Learning || Python ML PT.5
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47 Build FAST Machine Learning Apps with Javascript React.Js and Watson || Python ML PT.6
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48 Analyzing Twitter Accounts with Python and Personality Insights
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49 Converting Speech to Text in 10 Minutes with Python and Watson
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50 Build a Face Mask Detector in 20 Minutes with Watson and Python
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51 AI Text to Speech in 10 Minutes with Python and Watson TTS
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52 Pandas for Data Science in 20 Minutes | Python Crash Course
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53 Language Translation and Identification in 10 Minutes with Python and Watson AI
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54 Analyse ANY Conversation in 10 Minutes with Python and Watson Tone Analyser
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55 Deep Reinforcement Learning Tutorial for Python in 20 Minutes
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56 NumPy for Beginners in 15 minutes | Python Crash Course
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57 Real Time Pose Estimation with Tensorflow.Js and Javascript
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58 Transcribe Video to Text with Python and Watson in 15 Minutes
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59 Serverless Functions for TM1/Planning Analytics in 20 Minutes
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60 Building a AI Budget Bot for Planning Analytics with Watson Assistant in 20 Minutes
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This video teaches how to use IBM Watson's Visual Recognition service to build an image classifier, specifically using the food classifier to classify images of food. The tutorial provides a step-by-step guide on how to implement the classifier using Python. The key insight is that custom classifiers can be used to delve into more detailed classifications of specific objects, such as food.

Key Takeaways
  1. Replace the URL with the URL of the image to be classified
  2. Add an extra parameter to the classifier method to use a custom classifier
  3. Specify the classifier ID as 'food' to use the food classifier
  4. Run the cell again to see the classification results
💡 Custom classifiers can be used to delve into more detailed classifications of specific objects, such as food.

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