@Dtractus . Sorry for delay. I had to do some work in my backyard.. I modified your code. Somehow you don't needed this if w>50 and h>50:. This may occurred problem.

#!/usr/bin/python 37
#OpenCV 4.3.0, Raspberry Pi 3/B/4B-w/4/8GB RAM, Buster,v10.
#Date: 3rd, June, 2020

import cv2

# Load the image
img = cv2.imread('photos/testtt.png')

# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

edged = cv2.Canny(img, 170, 490)
# Apply adaptive threshold
thresh = cv2.adaptiveThreshold(edged, 255, 1, 1, 11, 2)
thresh_color = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)

# apply some dilation and erosion to join the gaps - change iteration to detect more or less area's
thresh = cv2.dilate(thresh,None,iterations = 15)
thresh = cv2.erode(thresh,None,iterations = 15)

# Find the contours
contours,hierarchy = cv2.findContours(thresh,
                                      cv2.RETR_TREE,
                                      cv2.CHAIN_APPROX_SIMPLE)

# For each contour, find the bounding rectangle and draw it
for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    cv2.rectangle(img,
                  (x,y),(x+w,y+h),
                  (0,255,0),
                  2)

    cv2.rectangle(thresh_color,
                  (x,y),(x+w,y+h),
                  (0,255,0),
                  2)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows(

Output:

@Dtractus . Sorry for delay. I had to do some work in my backyard.. I modified your code. Somehow you don't needed this if w>50 and h>50:. This may occurred problem.

#!/usr/bin/python 37
#OpenCV 4.3.0, Raspberry Pi 3/B/4B-w/4/8GB RAM, Buster,v10.
#Date: 3rd, June, 2020

import cv2

# Load the image
img = cv2.imread('photos/testtt.png')

# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

edged = cv2.Canny(img, 170, 490)
# Apply adaptive threshold
thresh = cv2.adaptiveThreshold(edged, 255, 1, 1, 11, 2)
thresh_color = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)

# apply some dilation and erosion to join the gaps - change iteration to detect more or less area's
thresh = cv2.dilate(thresh,None,iterations = 15)
thresh = cv2.erode(thresh,None,iterations = 15)

# Find the contours
contours,hierarchy = cv2.findContours(thresh,
                                      cv2.RETR_TREE,
                                      cv2.CHAIN_APPROX_SIMPLE)

# For each contour, find the bounding rectangle and draw it
for cnt in contours:
    x,y,w,h = cv2.boundingRect(cnt)
    cv2.rectangle(img,
                  (x,y),(x+w,y+h),
                  (0,255,0),
                  2)

    cv2.rectangle(thresh_color,
                  (x,y),(x+w,y+h),
                  (0,255,0),
                  2)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows(

Output:

@Dtractus . Sorry for delay. I had to do some work in my backyard.. I modified your code. Somehow you don't needed this if w>50 and h>50:. This may occurred problem.

 #!/usr/bin/python 37
 #OpenCV 4.3.0, Raspberry Pi 3/B/4B-w/4/8GB RAM, Buster,v10.
 #Date: 3rd, June, 2020

 import cv2

 # Load the image
 img = cv2.imread('photos/testtt.png')

 # convert to grayscale
 gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

 edged = cv2.Canny(img, 170, 490)
 # Apply adaptive threshold
 thresh = cv2.adaptiveThreshold(edged, 255, 1, 1, 11, 2)
 thresh_color = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)

 # apply some dilation and erosion to join the gaps - change iteration to detect more or less area's
 thresh = cv2.dilate(thresh,None,iterations = 15)
 thresh = cv2.erode(thresh,None,iterations = 15)

 # Find the contours
 contours,hierarchy = cv2.findContours(thresh,
                                       cv2.RETR_TREE,
                                       cv2.CHAIN_APPROX_SIMPLE)

 # For each contour, find the bounding rectangle and draw it
 for cnt in contours:
     x,y,w,h = cv2.boundingRect(cnt)
     cv2.rectangle(img,
                   (x,y),(x+w,y+h),
                   (0,255,0),
                   2)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

@Dtractus . Sorry for delay. I had to do some work in my backyard.. I modified your code. Somehow you don't needed this if w>50 and h>50:. This may occurred problem.

    #!/usr/bin/python 37
    #OpenCV 4.3.0, Raspberry Pi 3/B/4B-w/4/8GB RAM, Buster,v10.
    #Date: 3rd, June, 2020

    import cv2

    # Load the image
    img = cv2.imread('photos/testtt.png')

    # convert to grayscale
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    edged = cv2.Canny(img, 170, 490)
    # Apply adaptive threshold
    thresh = cv2.adaptiveThreshold(edged, 255, 1, 1, 11, 2)
    thresh_color = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)

    # apply some dilation and erosion to join the gaps - change iteration to detect more or less area's
    thresh = cv2.dilate(thresh,None,iterations = 15)
    thresh = cv2.erode(thresh,None,iterations = 15)

    # Find the contours
    contours,hierarchy = cv2.findContours(thresh,
                                          cv2.RETR_TREE,
                                          cv2.CHAIN_APPROX_SIMPLE)

    # For each contour, find the bounding rectangle and draw it
    for cnt in contours:
        x,y,w,h = cv2.boundingRect(cnt)
        cv2.rectangle(img,
                      (x,y),(x+w,y+h),
                      (0,255,0),
                      2)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Output:

#!/usr/bin/python 37
#OpenCV 4.3.0, Raspberry Pi 3/B/4B-w/4/8GB RAM, Buster,v10.
#Date: 5th, June, 2020

import cv2

# read and scale down image
img = cv2.pyrDown(cv2.imread('text3.jpg', cv2.IMREAD_UNCHANGED))

# threshold image
ret, threshed_img = cv2.threshold(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY),
                                  11, 55, cv2.THRESH_BINARY)

thresh = cv2.dilate(threshed_img, None, iterations = 5)
thresh = cv2.erode(threshed_img, None, iterations = 5)

contours, hier = cv2.findContours(thresh,
                                  cv2.RETR_EXTERNAL,
                                  cv2.CHAIN_APPROX_SIMPLE)

for c in contours:
    # get the bounding rect
    x, y, w, h = cv2.boundingRect(c)
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), thickness=1, lineType=8, shift=0)

cv2.imshow('contours', img)

while(cv2.waitKey()is not ord('q')):
    continue

cv2.destroyAllWindows()