kevinlinxc · March 23, 2024 19:00
diff --git a/keyboard_to_letter_contour.py b/keyboard_to_letter_contour.py
 from PIL import Image, ImageDraw, ImageFont
 import cv2
 import numpy as np

 def get_bounding_rect_area(contour):
    # calculate area using the minimum bounding rectangle instead of whatever cv2.contourArea does
    rect = cv2.minAreaRect(contour)
    width = rect[1][0]
    height = rect[1][1]
    return width * height


 def draw_biggest_external_contour(frame, 
                                  border_size=0, 
                                  border_color=(255, 255, 255), 
                                  min_distance=50, 
                                  canny_low=50, 
                                  canny_high=150, 
                                  dilate_kernel_size=10):
    # Add a white border to the frame, so that a fully black frame will still have an outline
    frame = cv2.copyMakeBorder(frame, border_size, border_size, border_size, border_size, cv2.BORDER_CONSTANT, value=border_color)
    
    # Convert the frame to grayscale
    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dilate_kernel_size, dilate_kernel_size))
    morphed = cv2.morphologyEx(gray_frame, cv2.MORPH_CLOSE, kernel)
    # dilate and erode to remove noise
    
    # Run Canny edge detection
    edges = cv2.Canny(morphed, canny_low, canny_high)
    
    # Find contours
    contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) # cv2.RETR_EXTERNAL for just external, 
    
    # Find the largest n contours
    if len(contours) == 0:
        return [], frame, 0
    main_contours = []
    # add all contours with area greater than 100
    for contour in contours:
        if get_bounding_rect_area(contour) > 200:
            main_contours.append(contour)
    # num_contours = len(main_contours)
    
    # Extract points along the contour that are farther than min_distance away from each other
    contour_points = []
    for main_contour in main_contours:
        for i in range(len(main_contour)):
            point = main_contour[i][0]
            # if i is 0 or if the the point is far enough from the previous point
            if i == 0 or np.linalg.norm(np.array(point) - np.array(contour_points[-1])) > min_distance:
                contour_points.append(tuple(point))

    # reduce duplicates 
    new_contour_points = []
    for i in range(len(contour_points)):
        if i == 0 or all(np.linalg.norm(np.array(contour_points[i]) - np.array(point)) > min_distance/3 for point in new_contour_points):
            new_contour_points.append(contour_points[i])
    contour_points = new_contour_points

    # Draw circles on the frame at the extracted points

    for point in contour_points:
        cv2.circle(frame, point, 8, (0, 255, 0), -1)

    
    return contour_points, frame

 if __name__ == "__main__":
    font_size = 500  # Increase the font size for a much bigger text
    font_filepath = "Lato-Black.ttf" # download a font to use, put it in the same directory
    text_color = (0, 0, 0, 255)  # RGBA format, where the last value is alpha (transparency)
    padding = 50  # Padding size in pixels

    # Initialize the font and mask image
    font = ImageFont.truetype(font_filepath, size=font_size)
    text = "A"  # Initial text
    text_width, text_height = font.getsize(text)
    padded_width = text_width + 2 * padding
    padded_height = text_height + 2 * padding
    mask_image = Image.new("RGBA", (padded_width, padded_height), (255, 255, 255, 255))  # Transparent background
    mask_draw = ImageDraw.Draw(mask_image)

    # Calculate the position to center the text horizontally
    text_x = (padded_width - text_width) // 2
    text_y = 0

    mask_draw.text((text_x, text_y), text, font=font, fill=text_color)  # Draw text with padding
    img = np.array(mask_image)
    contour_points, frame = draw_biggest_external_contour(img)

    last_letter = ord('A')
    cv2.imshow("test", frame)
    key = cv2.waitKey(0) & 0xFF

    while key != 27: # the ESC key
        print(key)
        if key != 255 and key != 1:  # default if no key is pressed, also 1 sometimes shows up for the first button?
            text = chr(key)

            # Clear the previous text in the mask image
            mask_draw.rectangle((0, 0, padded_width, padded_height), fill=(255, 255, 255, 255))

            # Calculate the position to center the new text horizontally
            text_width, text_height = font.getsize(text)
            text_x = (padded_width - text_width) // 2
            text_y = 0

            # Draw the new text in the mask image with padding
            mask_draw.text((text_x, text_y), text, font=font, fill=text_color)

            # Convert the updated mask image to a numpy array for OpenCV processing
            img = np.array(mask_image)
            contour_points, frame = draw_biggest_external_contour(img)

            # Display the updated image using OpenCV
            cv2.imshow("test", frame)
            last_letter = key
        key = cv2.waitKeyEx(0)

    cv2.destroyAllWindows()
	from PIL import Image, ImageDraw, ImageFont
	import cv2
	import numpy as np

	def get_bounding_rect_area(contour):
	# calculate area using the minimum bounding rectangle instead of whatever cv2.contourArea does
	rect = cv2.minAreaRect(contour)
	width = rect[1][0]
	height = rect[1][1]
	return width * height


	def draw_biggest_external_contour(frame,
	border_size=0,
	border_color=(255, 255, 255),
	min_distance=50,
	canny_low=50,
	canny_high=150,
	dilate_kernel_size=10):
	# Add a white border to the frame, so that a fully black frame will still have an outline
	frame = cv2.copyMakeBorder(frame, border_size, border_size, border_size, border_size, cv2.BORDER_CONSTANT, value=border_color)

	# Convert the frame to grayscale
	gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

	kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dilate_kernel_size, dilate_kernel_size))
	morphed = cv2.morphologyEx(gray_frame, cv2.MORPH_CLOSE, kernel)
	# dilate and erode to remove noise

	# Run Canny edge detection
	edges = cv2.Canny(morphed, canny_low, canny_high)

	# Find contours
	contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) # cv2.RETR_EXTERNAL for just external,

	# Find the largest n contours
	if len(contours) == 0:
	return [], frame, 0
	main_contours = []
	# add all contours with area greater than 100
	for contour in contours:
	if get_bounding_rect_area(contour) > 200:
	main_contours.append(contour)
	# num_contours = len(main_contours)

	# Extract points along the contour that are farther than min_distance away from each other
	contour_points = []
	for main_contour in main_contours:
	for i in range(len(main_contour)):
	point = main_contour[i][0]
	# if i is 0 or if the the point is far enough from the previous point
	if i == 0 or np.linalg.norm(np.array(point) - np.array(contour_points[-1])) > min_distance:
	contour_points.append(tuple(point))

	# reduce duplicates
	new_contour_points = []
	for i in range(len(contour_points)):
	if i == 0 or all(np.linalg.norm(np.array(contour_points[i]) - np.array(point)) > min_distance/3 for point in new_contour_points):
	new_contour_points.append(contour_points[i])
	contour_points = new_contour_points

	# Draw circles on the frame at the extracted points

	for point in contour_points:
	cv2.circle(frame, point, 8, (0, 255, 0), -1)


	return contour_points, frame

	if __name__ == "__main__":
	font_size = 500 # Increase the font size for a much bigger text
	font_filepath = "Lato-Black.ttf" # download a font to use, put it in the same directory
	text_color = (0, 0, 0, 255) # RGBA format, where the last value is alpha (transparency)
	padding = 50 # Padding size in pixels

	# Initialize the font and mask image
	font = ImageFont.truetype(font_filepath, size=font_size)
	text = "A" # Initial text
	text_width, text_height = font.getsize(text)
	padded_width = text_width + 2 * padding
	padded_height = text_height + 2 * padding
	mask_image = Image.new("RGBA", (padded_width, padded_height), (255, 255, 255, 255)) # Transparent background
	mask_draw = ImageDraw.Draw(mask_image)

	# Calculate the position to center the text horizontally
	text_x = (padded_width - text_width) // 2
	text_y = 0

	mask_draw.text((text_x, text_y), text, font=font, fill=text_color) # Draw text with padding
	img = np.array(mask_image)
	contour_points, frame = draw_biggest_external_contour(img)

	last_letter = ord('A')
	cv2.imshow("test", frame)
	key = cv2.waitKey(0) & 0xFF

	while key != 27: # the ESC key
	print(key)
	if key != 255 and key != 1: # default if no key is pressed, also 1 sometimes shows up for the first button?
	text = chr(key)

	# Clear the previous text in the mask image
	mask_draw.rectangle((0, 0, padded_width, padded_height), fill=(255, 255, 255, 255))

	# Calculate the position to center the new text horizontally
	text_width, text_height = font.getsize(text)
	text_x = (padded_width - text_width) // 2
	text_y = 0

	# Draw the new text in the mask image with padding
	mask_draw.text((text_x, text_y), text, font=font, fill=text_color)

	# Convert the updated mask image to a numpy array for OpenCV processing
	img = np.array(mask_image)
	contour_points, frame = draw_biggest_external_contour(img)

	# Display the updated image using OpenCV
	cv2.imshow("test", frame)
	last_letter = key
	key = cv2.waitKeyEx(0)

	cv2.destroyAllWindows()