Virtual reality controller for playing minecraft
- Modular to support addons
- Tangle free gaming since the entire system is wireless
- Minimal lag during gaming due to high-speed data transfer
- Product certifications: CE certified and ROHS compliant
import os | |
from tensorflow.python.profiler import profiler_client | |
tpu_profile_service_address = os.environ['COLAB_TPU_ADDR'].replace('8470', '8466') | |
print(profiler_client.monitor(tpu_profile_service_address, 100, 2)) |
import os | |
import shutil | |
import requests | |
import time | |
import random | |
# pip install requests-html | |
from requests_html import HTMLSession | |
session = HTMLSession() |
INGAME is a motion emulator with virtual reality features for playing first person shooting/adventure games. Virtual reality (VR) is a simulated experience that can be similar to or completely different from the real world. INGAME has been designed to provide the user with the feeling of being 'IN-the-GAME'. INGAME is modular in nature and consists of the following modules.
// A workaroud to use clear as a command to clear Command Prompt | |
// Step 1: g++ clear.cpp -o clear.exe | |
// Step 2: Add clear.exe directory to PATH enviroment variable | |
#include<cstdlib> | |
int main() { | |
system("cls"); | |
return 0; | |
} |
import sys | |
import serial | |
import serial.tools.list_ports as port_list | |
def serial_communication(): | |
ports = list(port_list.comports()) | |
if ports == []: | |
print("No open ports found!") | |
sys.exit() |
import os, glob, json | |
import cv2 | |
class BoundingBoxConvertor: | |
def __init__(self): | |
self.label_map = { | |
"0":"class1", | |
"1":"class2", | |
"2":"class3" | |
} |
import requests | |
headers = { | |
'User-Agent': "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.90 Safari/537.36" | |
} | |
def get_webpage(): | |
url = "www.google.com" | |
print(url) | |
response = requests.request("GET", url, headers=headers) |
import cv2 | |
import numpy as np | |
import time | |
greenHSVLowerLimit = (24, 76, 0) | |
greenHSVUpperLimit = (84, 255, 255) | |
VideoStream = cv2.VideoCapture(0) | |
time.sleep(2.0) |
import cv2 | |
import numpy as np | |
import matplotlib.pyplot as plt | |
image = cv2.imread("sample-images/minions.jpg") | |
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
plt.imshow(image) | |
pixel_values = image.reshape((-1, 3)) | |
pixel_values = np.float32(pixel_values) |