Ready Model

README.md

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+# Starting project
+
+## Step 1. Create Map
+First of all we have to create map for TF Dataset. Using DataSetLoader we have to provide path to images folder and call get_classified_csv(). This will create a Map (Image Path with label). 
+This will be later used for creating TF dataset.
+
+## Step 2. Create Dataset
+Then you can uncomment lines in main.py for generating dataset. Make sure that you have changed a path. Also change an image size, for this we have parameters like x and y. This way resized images will be saved to dataset. We recommend using x=35 and y=35. That's how you get the best results.
+
+## Step 3. Load datasets to kaggle
+Just create a new Dataset and move dataset_YxY after that add to notebook as input
+
+## Step 4. Evaluate in Kaggle
+Copy everything from Evaluator_Kaggle.ipynb in Notebook. Don't forget to turn on an GPU Accelarator. That way you will get result a lot faster.
+
+## Optional. Testing locally
+You can also train model and start tests locally. For that just start a main.py. Offcourse, don't forget to comment lines for creating a CSV and mapping. Also change a path to wished dataset.