Error

[Zyfroxx]

When i try to lauch AimI this happen

Aimbot : always on
Traceback (most recent call last):
File "C:\Users\guill\Downloads\AIMi-main\AIMi-main\start.py", line 20, in
inputs.aimbot(ENABLE_AIMBOT=True)
~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^
File "C:\Users\guill\Downloads\AIMi-main\AIMi-main\lib\detect.py", line 141, in aimbot
layerOutputs = net.forward(ln)
cv2.error: OpenCV(4.12.0) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\net_impl.cpp:120: error: (-215:Assertion failed) preferableBackend != DNN_BACKEND_CUDA || IS_DNN_CUDA_TARGET(preferableTarget) in function 'cv::dnn::dnn4_v20250619::Net::Impl::validateBackendAndTarget'
Any fix ?

[Loxsavvin09]

change detect.py to this: import sys
import time
import timeit
from termcolor import colored
from utils.grab import screen
import cv2
import imutils
import mss
import _thread
import ctypes
import os
import signal
import numpy as np
import pynput
import keyboard
from pynput.mouse import Listener
import winsound
sct = mss.mss()
Wd, Hd = sct.monitors[1]["width"], sct.monitors[1]["height"]
SendInput = ctypes.windll.user32.SendInput

def position(x, y):
x = 1 + int(x * 65536./Wd)
y = 1 + int(y * 65536./Hd)
extra = ctypes.c_ulong(0)
ii_ = pynput.util.win32.INPUT_union()
ii.mi = pynput._util.win32.MOUSEINPUT(x, y, 0, (0x0001 | 0x8000), 0, ctypes.cast(ctypes.pointer(extra), ctypes.c_void_p))
command=pynput.util.win32.INPUT(ctypes.c_ulong(0), ii)
SendInput(1, ctypes.pointer(command), ctypes.sizeof(command))

def aimbot(ENABLE_AIMBOT):

YOLO_DIRECTORY = "models" #yolo model path

CONFIDENCE = 0.36

THRESHOLD = 0.22

aimbot_paused = True #make aimbot off on startup

GREEN = '\033[92m'#dont touch it 

RED = '\033[91m'#dont touch it 

RESET = '\033[0m'#dont touch it 

ACTIVATION_RANGE = 250 #box in the center of your screen, lower value of pixel makes the capture faster, for example 250 mean 250x250 pixel box.

labelsPath = os.path.sep.join([YOLO_DIRECTORY, "coco-dataset.labels"])
LABELS = open(labelsPath).read().strip().split("\n")
np.random.seed(42)
COLORS = np.random.randint(0, 255, size=(len(LABELS), 3),
                           dtype="uint8")

weightsPath = os.path.sep.join([YOLO_DIRECTORY, "yolov3-tiny.weights"])#yolo path weights
configPath = os.path.sep.join([YOLO_DIRECTORY, "yolov3-tiny.cfg"])#yolo path models
time.sleep(0.4)

print("\033[1;36m[Status] loading objects detector..")
net = cv2.dnn.readNetFromDarknet(configPath, weightsPath)#load objects detector
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_OPENCV)   
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)        
ln = net.getLayerNames()
ln = [ln[i - 1] for i in net.getUnconnectedOutLayers()]


print("\033[1;36m[Status] Define screen capture area..")
W, H = None, None
origbox = (int(Wd/2 - ACTIVATION_RANGE/2),#gui box capture
           int(Hd/2 - ACTIVATION_RANGE/2),
           int(Wd/2 + ACTIVATION_RANGE/2),
           int(Hd/2 + ACTIVATION_RANGE/2))

if not ENABLE_AIMBOT:
    print(colored("[Status] aimbot disabled, only objects detector works...", "red"))
else:
    print(colored("[AI] Aimbot enabled..", "green"))

def signal_handler(sig, frame):
    print("\n[Exit] cleaning up...")
    sct.close()#quit and clear terminal
    cv2.destroyAllWindows()
    sys.exit(0)
signal.signal(signal.SIGINT, signal_handler)

build_info = str("".join(cv2.getBuildInformation().split()))#check if cpu and gpu cuda is working or disable.
if cv2.ocl.haveOpenCL():
    cv2.ocl.setUseOpenCL(True)
    cv2.ocl.useOpenCL()
    print(colored("[CPU] OpenCL is enabled..", "green"))
else:
    print(
        colored("[WARNING-CPU] OpenCL is disabled..", "yellow"))
if "CUDA:YES" in build_info:
    print(colored("[GPU] CUDA is enabled..", "green"))
else:
    print(
        colored("[WARNING-GPU] CUDA is disabled..", "yellow"))

print()

def toggle_aimbot():
    nonlocal aimbot_paused
    aimbot_paused = not aimbot_paused
    status = "hold mode" if aimbot_paused else "always on"
    color = RED if aimbot_paused else GREEN
    print("\nAimbot : " + color + status + RESET)
    if not aimbot_paused:
      duration = 100  
      freq = 440
      winsound.Beep(freq, duration)
keyboard.add_hotkey('F1', toggle_aimbot)


def on_click(x, y, button, pressed):
   
   if button == button.x2:
    nonlocal aimbot_paused
    aimbot_paused = not aimbot_paused
    if pressed:
        print("")
    else:
        print("")
with Listener(on_click=on_click) as listener:
 
 while True:
    if aimbot_paused:
        time.sleep(0.1)
        continue
    start_time = timeit.default_timer()
    frame = np.array(screen(region=origbox))
    frame = cv2.cvtColor(frame, cv2.COLOR_RGBA2BGR)
    if W is None or H is None:
        (H, W) = frame.shape[: 2]

    frame = cv2.UMat(frame)
    blob = cv2.dnn.blobFromImage(frame, 1 / 260, (150, 150),
                                 swapRB=False, crop=False)
    net.setInput(blob)
    layerOutputs = net.forward(ln)
    boxes = []
    confidences = []
    classIDs = []
    for output in layerOutputs:
        for detection in output:
            scores = detection[5:]
            # classID = np.argmax(scores)
            # confidence = scores[classID]
            classID = 0  # person = 0
            confidence = scores[classID]
            if confidence > CONFIDENCE:
                box = detection[0: 4] * np.array([W, H, W, H])
                (centerX, centerY, width, height) = box.astype("int")
                x = int(centerX - (width / 2))
                y = int(centerY - (height / 2))
                boxes.append([x, y, int(width), int(height)])
                confidences.append(float(confidence))
                classIDs.append(classID)
    idxs = cv2.dnn.NMSBoxes(boxes, confidences, CONFIDENCE, THRESHOLD)
    
    if len(idxs) > 0:
    
        bestMatch = confidences[np.argmax(confidences)]

        for i in idxs.flatten():
            (x, y) = (boxes[i][0], boxes[i][1])
            (w, h) = (boxes[i][2], boxes[i][3])
            cv2.circle(frame, (int(x + w / 2), int(y + h / 5)), 5, (0, 0, 255), -1) #draw target dot
            # color = [int(c) for c in COLORS[classIDs[i]]]
            cv2.rectangle(frame, (x, y), #draw a box rectangle
             (x + w, y + h), (0, 255, 0), 2)
            text = "Target {}%".format(int(confidences[i] * 100))
            cv2.putText(frame, text, (x, y - 8),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
            if ENABLE_AIMBOT and bestMatch == confidences[i]:
                mouseX = origbox[0] + (x + w/1.5)
                mouseY = origbox[1] + (y + h/5)
                position(mouseX, mouseY)

    cv2.imshow("Gui Objects Detector", frame)
    elapsed = timeit.default_timer() - start_time
    sys.stdout.write(
        "\033[1;33m\rFPS:{1} MS:{0}\t".format(int(elapsed*1000), int(1/elapsed)))
    sys.stdout.flush()
    if cv2.waitKey(1) & 0xFF == ord('0'):
        break

signal_handler(0, 0)
listener.join()