Update Phase1.md

Tutorial/Phase1.md

 This step prepares your project to render tailor-made images that will be later used for labeling the generates synthetic data.
 
 ### Step 3: Setup a Scene for Your Perception Simulation
-Simply put, in Unity, Scenes contain any object that exists in the world. This world can be a game, or in this case, a perception-oriented simulation. Every new project contains a Scene named _**SampleScene**_, which is automatically openned when the project is created. We will now modify this scene to remove the parts we will not need and tailor it to this tutorial.
+Simply put, in Unity, Scenes contain any object that exists in the world. This world can be a game, or in this case, a perception-oriented simulation. Every new project contains a Scene named `SampleScene`, which is automatically openned when the project is created. This Scenes comes with several objects and settings that we do not need, so let's create a new one. 
+
+* **Action**: In the _**Project**_ tab, right-click on the `Assets/Scenes` folder and click _**Create -> Scene**_. Name this new Scene `TutorialScene` and double-click on it to open it. 
-<img src="Images/hierarchy.png"/>
+<img src="Images/hierarchy.png" width="700"/>
-* **Action**: Delete everything shown in the hierarchy except for `Main Camera` and `Directional Light`. 
+As seen above, the new Scene already contains a camera (`Main Camera`) and a light (`Directional Light`). We will now modify the camera's field of view and position to prepare it for the tutorial. 
+
+* **Action**: Click on `Main Camera` and in the _**Inspector**_ tab, modify the camera's `Position`, `Rotation`, `Projection` and `Size` to match the screenshot below. (Note that `Size` only becomes available once you set `Projection` to `Orthographic`)
-To remove objects, select them and press `Delete` (Windows) or `cmd+delete` (Mac) on your keyboard. You can also right-click an object and click `Delete`. After this step, your Scene hierarchy should look like below: 
-<img src="Images/hierarchy_1.png" width="200"/>
+<img src="Images/camera_prep.png"/>
-We will now add the necessary components to the camera already present in the scene in order to equip it for the perception workflow. To do this, we need to add a `PerceptionCamera` component to the camera, and then define which types of ground-truth we wish to generate using this camera.
+* **Action**: Click on `Directional Light` and in the _**Inspector**_ tab, set the `Shadow Type` to `No Shadows`.
+
+We will now add the necessary components to the camera in order to equip it for the perception workflow. To do this, we need to add a `PerceptionCamera` component to it, and then define which types of ground-truth we wish to generate using this camera.
-* **Action**: Select `Main Camera` in the Scene hierarchy, then, in the _**Inspector**_ tab, click on the _**Add Component**_ button.
+* **Action**: Select `Main Camera` again and in _**Inspector**_ tab, click on the _**Add Component**_ button.
 * **Action**: Start typing `Perception Camera` in the search bar that appears, until the `Perception Camera` script is found, with a **#** icon to the left.
 * **Action**: Click on this script to add it as a component. Your camera is now a `Perception` camera.
 
   1 `candy_minipralines_lindt`
   2 `cereal_cheerios_honeynut`
   3 `cleaning_snuggle_henkel`
-  4 `craft_yarn_caron_01`
+  4 `craft_yarn_caron`
-  9 `snack_biscotti_ghiott_01`
+  9 `snack_biscotti_ghiott`
   10 `snack_granolabar_naturevalley`
 
 Once done, the _**Inspector**_ window for `TutorialIdLabelConfig` will look like this:
 
 The output dataset includes a large variety of information about various aspects of the active sensors in the Scene (currently only one), as well as the ground-truth generated by all active labelers. [This page](https://github.com/Unity-Technologies/com.unity.perception/blob/master/com.unity.perception/Documentation%7E/Schema/Synthetic_Dataset_Schema.md) provides a comprehensive explanation on the schema of this dataset. We strongly recommend having a look at the page once you have completed this tutorial.
 
-* **Action**: To get a quick feel of how the data is stored, open the folder whose name starts with `Dataset`. 
+* **Action**: To get a quick feel of how the data is stored, open the folder whose name starts with `Dataset`, then open the file named `captures_000.json`. This file contains the output from `BoundingBox2DLabeler`. The `captures` array contains the position and rotation of the sensor (camera), the position and rotation of the ego (sensor group, currently only one), and the annotations made by `BoundingBox2DLabeler` for all visible objects defined in its label configuration. For each visibile object, the annotations include:
+* `label_id`: The numerical id assigned to this object's label in the labeler's label configuration
+* `label_name`: The object's label, e.g. `candy_minipralines_lindt`
+* `instance_id`: Unique instance id of the object
+* `x` and `y`: Pixel coordinates of the top-left corner of the object's bounding box. (measured from the top-left corner of the image)
+* `width` and `height` of the object's bounding box.