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@@ -89,9 +89,40 @@ first by opening the DIGITS workspace we should see something like this
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### second the Collected Data
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#### for image classification
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- second the collected data using mobile camera then by resizing the collected data to be 256*256
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- by choosing `images` then `classification`.
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- adding our dataset url in this case using udacity workspace it will be `/data/kitchen`
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- as previous more setting can be done like Minimum samples per class or maximum samples per class or even the percentage of validation photos and testing photos
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- then by giving the dataset a name and choosing create :
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/dataset2.png)
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samples of the collected data :
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/sample1.JPG)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/sample2.JPG)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/sample3.JPG)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/sample4.JPG)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/sample5.JPG)
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#### the model
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- by choosing `images` then `classification`
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- now we can set the number of epochs, Snapshot interval, Base Learning Rate, Validation interval ....
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- by choosing one of the 3 networks provided LeNet, AlexNet and GoogLeNet in this case GoogLeNet gaved a better results than AlexNet.
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- giving the model a name the create.
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the 2 models results AlexNet and GoogLeNet
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/graph2.png)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/graph3.png)
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- by choosing images for test
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/test4.png)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/test5.png)
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![](https://github.com/mohamedsayedantar/Robotic-Inference/blob/master/images/test6.png)
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