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README.md

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```python test.py ```
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# Training on CPU
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I trained on GTX 1050. 1 epoch lasted 10 seconds approximately.
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I trained on a GTX 1050. 1 epoch lasted 10 seconds approximately.
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If you are using CPU, which I do not recommend, change the lines below in train.py:
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```
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with tf.Session() as sess:
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```
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# Data
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3 categories: Cucumber, eggplant and mushroom. 188 images from 3 categories were used in this project.
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# Steps
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1 ) Collecting images via [Google Image Download](https://github.com/hardikvasa/google-images-download). Only one object must be in the image.
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<img src = "https://github.com/MuhammedBuyukkinaci/Object-Classification-and-Localization-with-TensorFlow/blob/master/repository_images/Screenshot%20(35).png" width="800" height="400">
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</p>
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3 ) Data Augmentation (**create_training_data.py**). Mirroring with respect to x axis, mirroring with respect to y axis and adding noise were carried out. Hereby, data amount were 8-fold.
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3 ) Data Augmentation (**create_training_data.py**). Mirroring with respect to x axis, mirroring with respect to y axis and adding noise were carried out. Hereby, data amount is 8-fold.
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<p align="center">
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<img src = "https://github.com/MuhammedBuyukkinaci/Object-Classification-and-Localization-with-TensorFlow/blob/master/repository_images/sample.png" width="800" height="400">

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