Detección de contornos con semillas personalizadas usando Python – OpenCV

Python3

# Import modules
import cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
 
# Upload the image in the same directory and then run the code
# If image not found you may get an error
# Reading Image
road = cv2.imread('road_image.jpg')
 
# Making Copy of Image
road_copy = np.copy(road)
 
# Creating two black image of same size as original image
marker_image = np.zeros(road.shape[:2], dtype=np.int32)
segments = np.zeros(road.shape, dtype=np.uint8)
 
# Function to return tuple of colors
def create_rgb(i):
    x = np.array(cm.tab10(i))[:3]*255
    return tuple(x)
 
 
# Storing Colors
colors = []
 
# One color for each single digit
for i in range(10):
    colors.append(create_rgb(i))
 
# Global Variables
# Color Choices
# Number of markers
no_markers = 10
 
# Current markers
current_marker = 1
 
# Flag
marks_updated = False
 
# CALLBACK FUNCTION
def mouse_callback(event, x, y, flags, param):
    global marks_updated
 
    if event == cv2.EVENT_LBUTTONDOWN:
         
        # TRACKING FOR MARKERS
        cv2.circle(marker_image, (x, y), 5, (current_marker), -1)
         
        # DISPLAY ON USER IMAGE
        cv2.circle(road_copy, (x, y), 5, colors[current_marker], -1)
 
        marks_updated = True
 
 
# Naming the window and setting call back function to it
cv2.namedWindow('Road Image')
cv2.setMouseCallback('Road Image', mouse_callback)
 
while True:
   
    # Show the 2 windows
    cv2.imshow('WaterShed Segments', segments)
    cv2.imshow('Road Image', road_copy)
 
    # Close everything if Esc is pressed
    k = cv2.waitKey(1)
    if k == 27:
        break
 
    # Clear all colors and start over if 'c' is pressed
    elif k == ord('c'):
        road_copy = road.copy()
        marker_image = np.zeros(road.shape[0:2], dtype=np.int32)
        segments = np.zeros(road.shape, dtype=np.uint8)
 
    # If a number 0-9 is chosen index the color
    elif k > 0 and chr(k).isdigit():
         
        # chr converts to printable digit
        current_marker = int(chr(k))
 
    # If we clicked somewhere, call the watershed
    # algorithm on our chosen markers
    if marks_updated:
        marker_image_copy = marker_image.copy()
        cv2.watershed(road, marker_image_copy)
        segments = np.zeros(road.shape, dtype=np.uint8)
 
        for color_ind in range(no_markers):
           
            # COLORING SEGMENTS
            segments[marker_image_copy == (color_ind)] = colors[color_ind]
 
        marks_updated = False
 
# Destroy all the windows at the end
cv2.destroyAllWindows()