Improved Detection of Cropped Images in Google Chrome Dino Game using OpenCV
The Google Chrome Dino game is a popular endless runner game that can be played by simply opening a new tab in the Chrome browser when there is no internet connection. In this game, the player controls a dinosaur that runs automatically, and the player must make the dinosaur jump over obstacles such as small cacti, big cacti, and birds (pterodactyls).
One way to automate the game is by using computer vision techniques to detect obstacles and make the dinosaur jump automatically. However, the game window is relatively small, and the dinosaur and obstacles occupy only a small portion of the screen. To improve the accuracy of object detection, we can crop the image to focus on the relevant area of the screen.
Cropping the Image
To crop the image, we need to identify the region of interest (ROI) in the screen capture. In the Dino game, the ROI is the area where the dinosaur and obstacles are located. We can use the OpenCV library to identify the ROI and crop the image.
```python
import cv2
import numpy as np
# Load the screen capture
screen = cv2.imread('screen_capture.png')
# Define the ROI
x = 50
y = 300
w = 100
h = 70
roi = screen[y:y+h, x:x+w]
# Crop the image
cropped_image = roi
```
Detecting Obstacles
Once we have cropped the image, we can use computer vision techniques to detect obstacles. In this example, we will use thresholding and contour detection to identify obstacles.
```python
# Convert the image to grayscale
gray = cv2.cvtColor(cropped_image, cv2.COLOR_BGR2GRAY)
# Apply thresholding to the grayscale image
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
# Find contours in the thresholded image
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Draw contours on the original image
result = cv2.drawContours(cropped_image, contours, -1, (0, 255, 0), 2)
```
Making the Dinosaur Jump
Once we have detected obstacles, we can make the dinosaur jump automatically. In the Dino game, the dinosaur jumps when the space bar is pressed. We can use the PyAutoGUI library to simulate a space bar press.
```python
import pyautogui
# Check if obstacles are detected
if len(contours) > 0:
# Make the dinosaur jump
pyautogui.press('space')
```
By cropping the image and using computer vision techniques, we can improve the accuracy of obstacle detection in the Google Chrome Dino game. This can be useful for automating the game or for developing more advanced AI agents that can play the game at a high level.
References
- Google Chrome Dino game: https://chromedino.com/
- OpenCV library: https://opencv.org/
- PyAutoGUI library: https://pyautogui.readthedocs.io/en/latest/
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