Count Object Python

การพัฒนาโปรแกรมนับวัตถุในภาพ

การพัฒนาโปรแกรมตรวจนับวัตถุในภาพ (Count Object) ซึ่งมีขั้นตอนดังนี้   คลิกเพื่อโหลดภาพ

👉การเปิดข้อมูล (Read Data)

1. import cv2

2. import numpy as np

3. 
   

4. # Load the image

5. image_path = r"C:\Users\user\Desktop\777.JPG"

6. image = cv2.imread(image_path)

7. 
   

8. # Convert to grayscale

9. gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

10. 
    

11. # Apply thresholding to create a binary image

12. _, thresh = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY_INV)

13. 
    

14. # Find contours

15. contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

16. 
    

17. # Count objects

18. object_count = len(contours)

19. print(f"Number of objects detected: {object_count}")

20. 
    

21. # Draw contours

22. cv2.drawContours(image, contours, -1, (0, 255, 0), 2)

23. 
    

24. # Display result

25. cv2.imshow("Detected Objects", image)

26. cv2.imshow("gray", gray)

27. 
    

28. cv2.waitKey(0)

29. cv2.destroyAllWindows()

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👉การเปิดข้อมูล (Read Data)

1. import cv2

2. import numpy as np

3. 
   

4. # Load the image

5. image_path = r"C:\Users\user\Desktop\33.JPG"

6. image = cv2.imread(image_path)

7. 
   

8. # Convert image to HSV color space

9. hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

10. 
    

11. # Define lower and upper bounds for the green background

12. lower_green = np.array([35, 40, 40])

13. upper_green = np.array([85, 255, 255])

14. 
    

15. # Create mask for the green background

16. mask = cv2.inRange(hsv, lower_green, upper_green)

17. 
    

18. # Invert mask to keep only the white objects

19. mask_inv = cv2.bitwise_not(mask)

20. 
    

21. # Convert to grayscale

22. gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

23. 
    

24. # Apply the mask to the grayscale image

25. masked_gray = cv2.bitwise_and(gray, gray, mask=mask_inv)

26. 
    

27. # Apply thresholding to create a binary image

28. _, thresh = cv2.threshold(masked_gray, 200, 255, cv2.THRESH_BINARY)

29. 
    

30. # Find contours

31. contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

32. 
    

33. # Count objects

34. object_count = len(contours)

35. print(f"Number of objects detected: {object_count}")

36. 
    

37. # Draw contours

38. cv2.drawContours(image, contours, -1, (0, 255, 0), 2)

39. 
    

40. # Display result

41. cv2.imshow("Detected Objects", image)

42. cv2.waitKey(0)

43. cv2.destroyAllWindows()

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👉การเปิดข้อมูล (Read Data)

1. import cv2

2. import numpy as np

3. 
   

4. # Load the image

5. image_path = r"C:\Users\user\Desktop\color.JPG"

6. image = cv2.imread(image_path)

7. 
   

8. # Convert to HSV color space

9. hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

10. 
    

11. # Define the lower and upper bounds for black color in HSV

12. lower_black = np.array([0, 0, 0])       # Lower bound for black

13. upper_black = np.array([180, 255, 50])  # Upper bound for black

14. 
    

15. # Create mask for black color (binary image)

16. black_mask = cv2.inRange(hsv, lower_black, upper_black)

17. 
    

18. # Invert the mask so that black objects appear black (0) and the background is white (255)

19. binary_result = 255 - black_mask

20. 
    

21. # Apply thresholding to create a binary image (if needed)

22. _, thresh = cv2.threshold(binary_result, 100, 255, cv2.THRESH_BINARY_INV)

23. 
    

24. # Find contours

25. contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

26. 
    

27. # Count objects

28. object_count = len(contours)

29. print(f"Number of objects detected: {object_count}")

30. 
    

31. # Convert binary image to 3-channel BGR for drawing colored contours

32. binary_result_bgr = cv2.cvtColor(binary_result, cv2.COLOR_GRAY2BGR)

33. 
    

34. # Draw contours on the binary image

35. cv2.drawContours(binary_result_bgr, contours, -1, (0, 255, 0), 2)  # Draw contours in green

36. 
    

37. # Display results

38. cv2.imshow("Binary Mask with Contours", binary_result_bgr)

39. cv2.imshow("Detected Objects on Original Image", image)

40. cv2.waitKey(0)

41. cv2.destroyAllWindows()

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