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+# BLOB DETECTION Assignment
+
+## Introduction
+
+The supplementary python material is so that you’re familiar with the
+language itself. This tutorial is to learn about one specific library
+this team utilizes often: OpenCV and a common sensor we use in our
+projects: stereo camera.
+
+Why do we use a stereo camera?
+
+The primary reason is for depth estimation. Let’s say there is a human
+standing in the road and we want to stop before we hit him. You can
+imagine it would be useful to know how far we are from that person.
+Stereo cameras allow us to have this information. You can think of them
+as the “eyes” of a human driver.
+
+## Getting Started
+
+### Python Virtual Enviornment (venv)
+
+A common practice that most python programmers use is creating a virtual
+environment. This ensures we are running the correct version of a
+package regardless of what is already on the system.
+
+To create a virtual environment use the following command (you should
+already have python installed):
+
+`python3 -m venv venv`
+
+To activate the virtual environment:
+
+`source venv/bin/activate`
+
+### ZED SDK Installation (in a venv)
+
+[Download the ZED SDK](https://www.stereolabs.com/developers/release)
+
+[Install the python API](https://www.stereolabs.com/docs/app-development/python/install)
+
+The script to install the python API will be the ZED SDK installation
+folder, Make sure you install it while your in your activated virtual
+environment.
+
+Its recommended you at least install the sample tutorials that the ZED
+sdk provides as a reference for this assignment and any future projects
+using the ZED.
+
+## Project
+
+*P1*: Use the OpenCV library to detect the big green circle only. Draw a
+bounding box around it! Break down the elements that uniquely identify
+the target (the big green circle). It is highly recommended you use
+[this function](https://learnopencv.com/blob-detection-using-opencv-python-c/):
+
+![Image](./algos_a1.d/AL_OpenCv_A1_Image.png)
+
+Output should look like:
+
+![Image](./algos_a1.d/AL_Detected_Green_Circles.png)
+
+*P2*: Print out the image you were originally provided and place it far
+away from the ZED camera. Use the python ZED API and your code from P1
+to estimate the distance from the stereo camera to the target. Print
+this distance out.
+
+**Helpful Info**:
+
+- The ZED cameras can be found in room 701.
+- [How to use OpenCV with the ZED](https://www.stereolabs.com/docs/opencv/python)
+- [Depth Stabilization Parameters](https://www.stereolabs.com/docs/depth-sensing/depth-settings)
+
+*P3*: Once you are detecting the proper shape and the distance from it,
+measure the distance using a tape measure from the left lens of the zed
+to the object. Report the percent error of the true distance (tape
+measurer) and the estimated distance (your answer from P2).
+
+**Note**: Note: If the ZED is giving inaccurate readings that is because
+it has a falloff in accuracy at close ranges so try moving the image
+back.
+https://support.stereolabs.com/hc/en-us/articles/206953039-How-does-the-ZED-work
diff --git a/docs/contributors.md b/docs/contributors.md
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--- a/docs/contributors.md
+++ b/docs/contributors.md
@@ -4,3 +4,4 @@ Here is a list of the contributors who have helped in writing our
 documentation, huge shout-out to them!
 
 - Jacob Koziej (EE '25)
+- Isaiah Rivera (EE '25)