使用 OpenCV 和 Tesseract 对图像中的感兴趣区域 (ROI) 进行 OCR

# Importing necessary librariesimport numpy as npimport cv2import mathfrom scipy import ndimageimport pytesseract

IMAGE_FILE_LOCATION = "test_image.jpg" # Photo by Amanda Jones on Unsplashinput_img = cv2.imread(IMAGE_FILE_LOCATION) # image read

###################################################################################################### ORIENTATION CORRECTION/ADJUSTMENT
def orientation_correction(img, save_image = False):    # GrayScale Conversion for the Canny Algorithm  img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)     # Canny Algorithm for edge detection was developed by John F. Canny not Kennedy!! :)img_edges = cv2.Canny(img_gray, 100, 100, apertureSize=3)    # Using Houghlines to detect lineslines = cv2.HoughLinesP(img_edges, 1, math.pi / 180.0, 100, minLineLength=100, maxLineGap=5)
    # Finding angle of lines in polar coordinatesangles = []for x1, y1, x2, y2 in lines[0]:angle = math.degrees(math.atan2(y2 - y1, x2 - x1))angles.append(angle)
    # Getting the median anglemedian_angle = np.median(angles)
    # Rotating the image with this median angleimg_rotated = ndimage.rotate(img, median_angle)
if save_image:cv2.imwrite('orientation_corrected.jpg', img_rotated)return img_rotated#####################################################################################################
img_rotated = orientation_correction(input_img)

###################################################################################################### REGION OF INTEREST (ROI) SELECTION
# initializing the list for storing the coordinates coordinates = [] 
# Defining the event listener (callback function)def shape_selection(event, x, y, flags, param):# making coordinates globalglobal coordinates 
# Storing the (x1,y1) coordinates when left mouse button is pressed  if event == cv2.EVENT_LBUTTONDOWN:         coordinates = [(x, y)] 
# Storing the (x2,y2) coordinates when the left mouse button is released and make a rectangle on the selected regionelif event == cv2.EVENT_LBUTTONUP:         coordinates.append((x, y)) 
# Drawing a rectangle around the region of interest (roi)        cv2.rectangle(image, coordinates[0], coordinates[1], (0,0,255), 2)         cv2.imshow("image", image) 

# load the image, clone it, and setup the mouse callback function image = img_rotatedimage_copy = image.copy()cv2.namedWindow("image") cv2.setMouseCallback("image", shape_selection) 

# keep looping until the 'q' key is pressed while True: # display the image and wait for a keypress     cv2.imshow("image", image)     key = cv2.waitKey(1) & 0xFF
if key==13: # If 'enter' is pressed, apply OCRbreak
if key == ord("c"): # Clear the selection when 'c' is pressed         image = image_copy.copy() 
if len(coordinates) == 2:     image_roi = image_copy[coordinates[0][1]:coordinates[1][1],                                coordinates[0][0]:coordinates[1][0]]     cv2.imshow("Selected Region of Interest - Press any key to proceed", image_roi)     cv2.waitKey(0) 
# closing all open windows cv2.destroyAllWindows()  
#####################################################################################################

##################################################################### OPTICAL CHARACTER RECOGNITION (OCR) ON ROItext = pytesseract.image_to_string(image_roi)print("The text in the selected region is as follows:")print(text)

"Isn't it a greenhouse?”