From 32df66afceaeb8f558096c5676fd626cfe7358fd Mon Sep 17 00:00:00 2001 From: Navan Chauhan Date: Wed, 29 Jan 2020 11:14:30 +0530 Subject: Publish deploy 2020-01-29 11:14 --- posts/2019-12-10-TensorFlow-Model-Prediction/index.html | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'posts/2019-12-10-TensorFlow-Model-Prediction/index.html') diff --git a/posts/2019-12-10-TensorFlow-Model-Prediction/index.html b/posts/2019-12-10-TensorFlow-Model-Prediction/index.html index 7b4d177..3b71ea8 100644 --- a/posts/2019-12-10-TensorFlow-Model-Prediction/index.html +++ b/posts/2019-12-10-TensorFlow-Model-Prediction/index.html @@ -1,4 +1,4 @@ -Making Predictions using Image Classifier (TensorFlow) | Navan Chauhan
Navan Chauhan
🕑 1 minute read.

Making Predictions using Image Classifier (TensorFlow)

This was tested on TF 2.x and works as of 2019-12-10

If you want to understand how to make your own custom image classifier, please refer to my previous post.

If you followed my last post, then you created a model which took an image of dimensions 50x50 as an input.

First we import the following if we have not imported these before

import cv2
+Making Predictions using Image Classifier (TensorFlow) | Navan Chauhan
Navan Chauhan
🕑 1 minute read.
Making Predictions using Image Classifier (TensorFlow)
This was tested on TF 2.x and works as of 2019-12-10
If you want to understand how to make your own custom image classifier, please refer to my previous post.
If you followed my last post, then you created a model which took an image of dimensions 50x50 as an input.
First we import the following if we have not imported these before
import cv2
 import os
 

 
@@ -20,4 +20,4 @@
 
Finally we make the prediction
print(['Infected','Uninfected'][np.argmax(model.predict(img))])
 

 
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Infected
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+

Infected

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