Merge pull request #2983 from JdeRobot/remove-old-instructions

Remove old docker instructions

_pages/exercises/AutonomousCars/car-junction.md

@@ -64,63 +64,9 @@ youtubeId: 4WIi2cpaLDA
 
 The goal of this practice is to implement the logic of a navigation algorithm for an automated vehicle. The vehicle must Stop at the T joint, where there is a stop sign, wait until there are no cars and pass once the road is clear.
 
-{% include gallery caption="Gallery" %}
-
-## Instructions
-This is the preferred way for running the exercise.
-
-### Installing and Launching
-1. Download [Docker](https://docs.docker.com/get-docker/). Windows users should choose WSL 2 backend Docker installation if possible, as it has better performance than Hyper-V.
-
-2. Pull the current distribution of RoboticsBackend:
-
-	```bash
-  docker pull jderobot/robotics-backend:latest
-  ```
-
-- In order to obtain optimal performance, Docker should be using multiple CPU cores. In case of Docker for Mac or Docker for Windows, the VM should be assigned a greater number of cores.
-
-- It is recommended to use the latest image. However, older distributions of RoboticsBackend can be found [here](https://hub.docker.com/r/jderobot/robotics-backend/tags).
-
-### How to perform the exercises?
-- Start a new docker container of the image and keep it running in the background:
-
-	```bash
-  docker run --rm -it -p 7164:7164 -p 2303:2303 -p 1905:1905 -p 8765:8765 -p 6080:6080 -p 1108:1108 -p 7163:7163 jderobot/robotics-backend
-  ```
-
-- On the local machine navigate to 127.0.0.1:7164/ in the browser and choose the desired exercise.
-
-- Wait for the Connect button to turn green and display "Connected". Click on the "Launch" button and wait for some time until an alert appears with the message `Connection Established` and button displays "Ready". 
-
-- The exercise can be used after the alert.
+**Note**: If you haven't, take a look at the [user guide](https://jderobot.github.io/RoboticsAcademy/user_guide/#installation) to understand how the installation is made, how to launch a RoboticsBackend and how to perform the exercises.
 
-### Enable GPU Acceleration
-- Follow the advanced launching instructions from [here](https://jderobot.github.io/RoboticsAcademy/user_guide/#enable-gpu-acceleration).
-
-**Where to insert the code?**
-
-In the launched webpage, type your code in the text editor,
-
-```python
-from GUI import GUI
-from HAL import HAL
-# Enter sequential code!
-
-
-while True:
-    # Enter iterative code!
-```
-
-### Using the Interface
-
-* **Control Buttons**: The control buttons enable the control of the interface. Play button sends the code written by User to the Robot. Stop button stops the code that is currently running on the Robot. Save button saves the code on the local machine. Load button loads the code from the local machine. Reset button resets the simulation (primarily, the position of the robot).
-
-* **Brain and GUI Frequency**: This input shows the running frequency of the iterative part of the code (under the `while True:`). A smaller value implies the code runs less number of times. A higher value implies the code runs a large number of times. The numerator is the one set as the Measured Frequency who is the one measured by the computer (a frequency of execution the computer is able to maintain despite the commanded one) and the input (denominator) is the Target Frequency which is the desired frequency by the student. The student should adjust the Target Frequency according to the Measured Frequency.
-
-* **RTF (Real Time Factor)**: The RTF defines how much real time passes with each step of simulation time. A RTF of 1 implies that simulation time is passing at the same speed as real time. The lower the value the slower the simulation will run, which will vary depending on the computer. 
-
-* **Pseudo Console**: This shows the error messages related to the student's code that is sent. In order to print certain debugging information on this console. The student can use the print() command in the Editor. 
+{% include gallery caption="Gallery" %}
 
 ## Robot API
 

_pages/exercises/AutonomousCars/global_navigation.md

@@ -124,61 +124,7 @@ The solution can integrate one or more of the following levels of difficulty, as
 
 * Arrive as quickly as possible to the destination.
 
-## Instructions
-This is the preferred way for running the exercise.
-
-### Installing and Launching
-1. Download [Docker](https://docs.docker.com/get-docker/). Windows users should choose WSL 2 backend Docker installation if possible, as it has better performance than Hyper-V.
-
-2. Pull the current distribution of RoboticsBackend:
-
-	```bash
-  docker pull jderobot/robotics-backend:latest
-  ```
-
-- In order to obtain optimal performance, Docker should be using multiple CPU cores. In case of Docker for Mac or Docker for Windows, the VM should be assigned a greater number of cores.
-
-- It is recommended to use the latest image. However, older distributions of RoboticsBackend can be found [here](https://hub.docker.com/r/jderobot/robotics-backend/tags).
-
-### How to perform the exercises?
-- Start a new docker container of the image and keep it running in the background:
-
-	```bash
-  docker run --rm -it -p 7164:7164 -p 2303:2303 -p 1905:1905 -p 8765:8765 -p 6080:6080 -p 1108:1108 -p 7163:7163 jderobot/robotics-backend
-  ```
-
-- On the local machine navigate to 127.0.0.1:7164/ in the browser and choose the desired exercise.
-
-- Wait for the Connect button to turn green and display "Connected". Click on the "Launch" button and wait for some time until an alert appears with the message `Connection Established` and button displays "Ready". 
-
-- The exercise can be used after the alert.
-
-### Enable GPU Acceleration
-- Follow the advanced launching instructions from [here](https://jderobot.github.io/RoboticsAcademy/user_guide/#enable-gpu-acceleration).
-
-**Where to insert the code?**
-
-In the launched webpage, type your code in the text editor,
-
-```python
-import GUI
-import HAL
-# Enter sequential code!
-
-
-while True:
-    # Enter iterative code!
-```
-
-### Using the Interface
-
-* **Control Buttons**: The control buttons enable the control of the interface. Play button sends the code written by User to the Robot. Stop button stops the code that is currently running on the Robot. Save button saves the code on the local machine. Load button loads the code from the local machine. Reset button resets the simulation(primarily, the position of the robot).
-
-* **Brain and GUI Frequency**: This input shows the running frequency of the iterative part of the code (under the `while True:`). A smaller value implies the code runs less number of times. A higher value implies the code runs a large number of times. The numerator is the one set as the Measured Frequency who is the one measured by the computer (a frequency of execution the computer is able to maintain despite the commanded one) and the input (denominator) is the Target Frequency which is the desired frequency by the student. The student should adjust the Target Frequency according to the Measured Frequency.
-
-* **RTF (Real Time Factor)**: The RTF defines how much real time passes with each step of simulation time. A RTF of 1 implies that simulation time is passing at the same speed as real time. The lower the value the slower the simulation will run, which will vary depending on the computer. 
-
-* **Pseudo Console**: This shows the error messages related to the student's code that is sent. In order to print certain debugging information on this console. The student can use the `print()` command in the Editor. 
+**Note**: If you haven't, take a look at the [user guide](https://jderobot.github.io/RoboticsAcademy/user_guide/#installation) to understand how the installation is made, how to launch a RoboticsBackend and how to perform the exercises.
 
 ## Robot API
 

_pages/exercises/AutonomousCars/qualifying_formula1.md

@@ -38,3 +38,4 @@ Program a Formula1 car to autonomously complete a lap to the Nürburgring circui
 
 {% include youtubePlayer.html id=page.youtubeId %}
 
+**Note**: If you haven't, take a look at the [user guide](https://jderobot.github.io/RoboticsAcademy/user_guide/#installation) to understand how the installation is made, how to launch a RoboticsBackend and how to perform the exercises.

_pages/exercises/ComputerVision/3d_reconstruction.md

@@ -61,61 +61,7 @@ In this practice, the intention is to program the necessary logic to allow kobuk
 
 {% include gallery caption="Scene to reconstruct" %}
 
-## Instructions
-This is the preferred way for running the exercise.
-
-### Installing and Launching
-1. Download [Docker](https://docs.docker.com/get-docker/). Windows users should choose WSL 2 backend Docker installation if possible, as it has better performance than Hyper-V.
-
-2. Pull the current distribution of RoboticsBackend:
-
-	```bash
-  docker pull jderobot/robotics-backend:latest
-  ```
-
-- In order to obtain optimal performance, Docker should be using multiple CPU cores. In case of Docker for Mac or Docker for Windows, the VM should be assigned a greater number of cores.
-
-- It is recommended to use the latest image. However, older distributions of RoboticsBackend can be found [here](https://hub.docker.com/r/jderobot/robotics-backend/tags).
-
-### How to perform the exercises?
-- Start a new docker container of the image and keep it running in the background:
-
-	```bash
-  docker run --rm -it -p 7164:7164 -p 2303:2303 -p 1905:1905 -p 8765:8765 -p 6080:6080 -p 1108:1108 -p 7163:7163 jderobot/robotics-backend
-  ```
-
-- On the local machine navigate to 127.0.0.1:7164/ in the browser and choose the desired exercise.
-
-- Wait for the Connect button to turn green and display "Connected". Click on the "Launch" button and wait for some time until an alert appears with the message `Connection Established` and button displays "Ready". 
-
-- The exercise can be used after the alert.
-
-### Enable GPU Acceleration
-- Follow the advanced launching instructions from [here](https://jderobot.github.io/RoboticsAcademy/user_guide/#enable-gpu-acceleration).
-
-**Where to insert the code?**
-
-In the launched webpage, type your code in the text editor,
-
-```python
-from GUI import GUI
-from HAL import HAL
-# Enter sequential code!
-
-
-while True:
-    # Enter iterative code!
-```
-
-### Using the Interface
-
-* **Control Buttons**: The control buttons enable the control of the interface. Play button sends the code written by User to the Robot. Stop button stops the code that is currently running on the Robot. Save button saves the code on the local machine. Load button loads the code from the local machine. Reset button resets the simulation (primarily, the position of the robot).
-
-* **Brain and GUI Frequency**: This input shows the running frequency of the iterative part of the code (under the `while True:`). A smaller value implies the code runs less number of times. A higher value implies the code runs a large number of times. The numerator is the one set as the Measured Frequency who is the one measured by the computer (a frequency of execution the computer is able to maintain despite the commanded one) and the input (denominator) is the Target Frequency which is the desired frequency by the student. The student should adjust the Target Frequency according to the Measured Frequency.
-
-* **RTF (Real Time Factor)**: The RTF defines how much real time passes with each step of simulation time. A RTF of 1 implies that simulation time is passing at the same speed as real time. The lower the value the slower the simulation will run, which will vary depending on the computer. 
-
-* **Pseudo Console**: This shows the error messages related to the student's code that is sent. In order to print certain debugging information on this console. The student can use the print() command in the Editor. 
+**Note**: If you haven't, take a look at the [user guide](https://jderobot.github.io/RoboticsAcademy/user_guide/#installation) to understand how the installation is made, how to launch a RoboticsBackend and how to perform the exercises.
 
 ## Robot API
 

_pages/exercises/ComputerVision/basic_computer_vision.md

@@ -38,13 +38,10 @@ In this practice the intention is to develop some basic exercises about computer
 
 **Note**: If you haven't, take a look at the [user guide](https://jderobot.github.io/RoboticsAcademy/user_guide/#installation) to understand how the installation is made, how to launch a RoboticsBackend and how to perform the exercises.
 
+## Exercise API
 
-## Robot API
-
-* `from HAL import HAL` - to import the HAL library class. This class contains the functions that receives information from the webcam.
-* `HAL.getImage()` - to get the image
-* `HAL.showImage()` - allows you to view a debug image or with relevant information
-
+* `GUI.getImage()` - to get the image. It can be None
+* `GUI.showImage()` - allows you to view a debug image or with relevant information
 
 ## Theory
 In this exercise it is proposed to implement different computer vision functionalities: