1# objectImageIdentifierAI
 2
 3- imagesToDataset
 4    - From two directories ('object' and 'noobject'), gets all the images inside the directories and generates the dataset
 5- nnTrain
 6    - From the dataset file generated in the previous step, train the Neural Network
 7- serverPredictor
 8    - Runs a server API, that with the Neural Network classifies the incoming images
 9- smartphoneApp
10    - Take photo and upload to the server, to get the response (object or no object)
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12![hotdognohotdog](https://raw.githubusercontent.com/arnaucode/objectImageIdentifierAI/master/hotdognohotdog.png "hotdognohotdog")
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15## Real steps
16- download images
17    - for example, can be done with https://github.com/arnaucode/imgDownloader.git
18- In /serverPredictor directory
19```
20python classifierChooser.py
21```
22This will generate the model.pkl. Then, run the serverPredictor.py
23```
24python serverPredictor.py
25```