Untitled

import cv2

from ultralytics import YOLO

import numpy as np

import board

import busio

from adafruit_mlx90640 import MLX90640

import time

 

# Initialize I2C for MLX90640

i2c = busio.I2C(board.SCL, board.SDA)

mlx = MLX90640(i2c)

#mlx.refresh_rate = MLX90640.RefreshRate.REFRESH_8_HZ

mlx.refresh_rate = 8 # 8 Hz refresh rate

 

# Initialize the USB camera

camera = cv2.VideoCapture(0) # Use 0 for the default camera, or adjust if needed

if not camera.isOpened():

print("Camera not detected. Exiting...")

exit()

 

#camera.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)

#camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

 

camera.set(cv2.CAP_PROP_FRAME_WIDTH, 640)

camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)

 

# Load YOLOv8 model

#model = YOLO("yolov8n_ncnn_model") # Use the correct path to your YOLOv8 model

model = YOLO("yolov8n.pt") # Use the correct path to your YOLOv8 model

 

# MLX90640 configuration

mlx_shape = (24, 32) # MLX90640 thermal resolution

thermal_data = np.zeros(mlx_shape[0] * mlx_shape[1])

 

prev_time = time.time() # To store the previous time for FPS calculation

 

while True:

# Capture a frame from the USB camera

ret, frame = camera.read()

if not ret:

print("Failed to capture frame. Exiting...")

break

 

# Run YOLO model on the captured frame

results = model.predict(frame, stream=False)

 

# Read temperature data from MLX90640

try:

mlx.getFrame(thermal_data)

thermal_array = np.reshape(thermal_data, mlx_shape)

except ValueError:

print("MLX90640 data error. Skipping this frame...")

continue

 

annotated_frame = frame.copy()

 

for detection in results:

# Get bounding box coordinates

x1, y1, x2, y2 = map(int, detection.boxes.xyxy[0].numpy())

 

# Crop the thermal data to the bounding box region

thermal_x1 = int(x1 * mlx_shape[1] / frame.shape[1])

thermal_y1 = int(y1 * mlx_shape[0] / frame.shape[0])

thermal_x2 = int(x2 * mlx_shape[1] / frame.shape[1])

thermal_y2 = int(y2 * mlx_shape[0] / frame.shape[0])

 

# Ensure indices are within bounds

thermal_x1 = max(0, min(thermal_x1, mlx_shape[1] - 1))

thermal_y1 = max(0, min(thermal_y1, mlx_shape[0] - 1))

thermal_x2 = max(0, min(thermal_x2, mlx_shape[1] - 1))

thermal_y2 = max(0, min(thermal_y2, mlx_shape[0] - 1))

 

# Get average temperature in the bounding box region

bbox_thermal_data = thermal_array[thermal_y1:thermal_y2, thermal_x1:thermal_x2]

avg_temperature = np.mean(bbox_thermal_data) if bbox_thermal_data.size > 0 else 0

 

# Prepare temperature text

temp_text = f"{avg_temperature:.1f} C"

 

# Draw the bounding box

cv2.rectangle(annotated_frame, (x1, y1), (x2, y2), (0, 255, 0), 2)

 

# Display temperature

cv2.putText(annotated_frame, temp_text, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)

 

# Calculate FPS

curr_time = time.time()

fps = 1 / (curr_time - prev_time) # FPS calculation

prev_time = curr_time

 

# Display FPS in the upper right corner with decimal precision

cv2.putText(annotated_frame, f"FPS: {fps:.2f}", (frame.shape[1] - 120, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)

 

# Display the annotated frame

cv2.imshow("Object Detection With MLX", annotated_frame)

 

# Exit the program if 'q' is pressed

if cv2.waitKey(1) == ord("q"):

break

 

# Release the camera and close all windows

camera.release()

cv2.destroyAllWindows()