model/ExampleUsage.py

try:
    import subprocess
except:
    print('"subprocess" module is not available, exiting...')
    exit()
try:
    import sys
except:
    print('"sys" module is not available, exiting...')
    exit()
try:
    import time
except:
    print('"time" module is not available, exiting...')
    exit()
try:
    import os
except:
    print('"os" module is not available, exiting...')
    exit()
try:
    import numpy as np
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "numpy"])
    import numpy as np
try:
    import pyautogui
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "pyautogui"])
    import pyautogui
try:
    import dxcam
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "dxcam"])
    import dxcam
try:
    import torch
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "torch"])
    import torch
try:
    import cv2
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "opencv-python"])
    import cv2
try:
    import pathlib
except:
    subprocess.check_call([sys.executable, "-m", "pip", "install", "pathlib"])
    import pathlib

temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

current_file_path = os.path.dirname(os.path.abspath(__file__))
model_path = os.path.join(current_file_path, 'best.pt')
model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, force_reload=True)

screen_width, screen_height = pyautogui.size()
camera = dxcam.create(device_idx=0,output_color="RGB")

cv2.namedWindow('YOLOv5 Detection', cv2.WINDOW_NORMAL)
cv2.resizeWindow('YOLOv5 Detection', 960, 540)
cv2.setWindowProperty('YOLOv5 Detection', cv2.WND_PROP_TOPMOST, 1)

while True:
    start_time = time.time()
    frame = camera.grab(region=(0, 0, screen_width, screen_height))
    if frame is None: continue
    rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)  

    results = model(rgb_frame)

    boxes = results.pandas().xyxy[0]

    for _, box in boxes.iterrows():
        label = box['name']
        score = box['confidence']
        x, y, w, h = int(box['xmin']), int(box['ymin']), int(box['xmax'] - box['xmin']), int(box['ymax'] - box['ymin'])
        
        if label in ['map']:
            cv2.rectangle(rgb_frame, (x, y), (x + w, y + h), (0, 255, 255), 3)
            cv2.putText(rgb_frame, f"{score:.2f}", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0, 255, 255), 2, cv2.LINE_AA)
        if label in ['arrow']:
            cv2.rectangle(rgb_frame, (x, y), (x + w, y + h), (255, 0, 0), 3)
            cv2.putText(rgb_frame, f"{score:.2f}", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (255, 0, 0), 2, cv2.LINE_AA)

    fps = round(1 / (time.time() - start_time), 1)
    cv2.putText(rgb_frame, f"fps: {fps}", (20, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2, cv2.LINE_AA)         
    cv2.imshow('YOLOv5 Detection', rgb_frame)
    cv2.resizeWindow('YOLOv5 Detection', 854, 480)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()