Update end-to-end README.md
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#### Training with Real Data
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To train with real data, the file [end-to-end/options/train_drunet.json](../end-to-end/options/train_drunet.json) must have the value __"drunet_finetune"__ in the *dataset_type* field (datasets-->train).
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To train with real data, the file [train_drunet.json](../end-to-end/options/train_drunet.json) must have the value __"drunet_finetune"__ in the *dataset_type* field (datasets-->train).
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#### Training with Synthetic Data
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To train with synthetic data, the file end-to-end/options/train_drunet.json](../end-to-end/options/train_drunet.json) must have the value __"drunet"__ in the *dataset_type* field (datasets-->train).
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To train with synthetic data, the file [train_drunet.json](../end-to-end/options/train_drunet.json) must have the value __"drunet"__ in the *dataset_type* field (datasets-->train).
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Once the data type was selected, use the following command to train the network:
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```
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### Generating Synthetic Captures
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For synthetic captured images generation, first configure the options on [tempest_simulation.json](end-to-end/options/tempest_simulation.json) file. Be sure to include the path to the folder containing the images to run the simulation of direct capturing image from the EME of a monitor. Then run the following command:
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For synthetic captured images generation, first configure the options on [tempest_simulation.json](../end-to-end/options/tempest_simulation.json) file. Be sure to include the path to the folder containing the images to run the simulation of direct capturing image from the EME of a monitor. Then run the following command:
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```shell
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python folder_simulation.py
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