diff --git a/README.md b/README.md
index ba81207..4fd096f 100644
--- a/README.md
+++ b/README.md
@@ -21,7 +21,7 @@ cd rewards-farmer
 
 You should also have an Ollama account created (for the LLM), the `ollama` tool installed, and you should have signed in to the Ollama CLI via the command line using `ollama signin`. This project will use a minimal amount of Ollama cloud usage using `gemma4:cloud`. If you wish to use a different model, please change the `model` parameter in the `get_ollama_response` function in `src/llm_utils.py`.
 
-You must also provide an image for the script to upload to complete the visual search task. Currently, this image is named `keypress_times.png` and is located in the root directory of the project (yes, I used a random image from my keyboard analysis to do this). You may provide an image of your own, just ensure that the absolute path of the image is placed in the `VISUAL_SEARCH_IMAGE_PATH` constant at the top of `rewards_tasks.py`.
+You must also provide an image for the script to upload to complete the visual search task. A helper script is included at `src/random_image.py` that will download an image named `random_image.png` into the project root for you. You may also provide an image of your own, just ensure that the absolute path of the image is placed in the `VISUAL_SEARCH_IMAGE_PATH` constant at the top of `rewards_tasks.py`.
 
 Activate the virtual environment & install dependencies (you may have to use `python -m poetry` instead of `poetry`).
 You must have Python 3.14+ and Poetry installed.
diff --git a/src/rewards_tasks.py b/src/rewards_tasks.py
index 1bdeeec..dd0bc32 100644
--- a/src/rewards_tasks.py
+++ b/src/rewards_tasks.py
@@ -15,7 +15,7 @@ import mouse_trajectory
 import mimic_typing
 import element_selectors
 
-VISUAL_SEARCH_IMAGE_PATH = os.path.abspath("keypress_times.png")
+VISUAL_SEARCH_IMAGE_PATH = os.path.abspath("random_image.png")
 
 class RewardsTaskUtils:
 	def __init__(self, driver: webdriver.Edge):