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deep-tempest
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Update end-to-end README.md

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@ -26,11 +26,11 @@ python tempest_evaluation.py
#### Training with Real Data #### Training with Real Data
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). 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).
#### Training with Synthetic Data #### Training with Synthetic Data
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). 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).
Once the data type was selected, use the following command to train the network: Once the data type was selected, use the following command to train the network:
@ -39,7 +39,7 @@ python main_train_drunet.py
``` ```
### Generating Synthetic Captures ### Generating Synthetic Captures
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: 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:
```shell ```shell
python folder_simulation.py python folder_simulation.py