我想尝试拍摄此图片中的要点:
并将它们转移到美国地图大纲:
但我正在努力。
我正在尝试使用一种方法来读取' data.png'中的非绿色像素的颜色和坐标位置,将它们存储在列表中,然后将这些像素放在& #39; us_outline.png'根据他们的位置。
这是我到目前为止的代码:
#IMPORTS
from __future__ import division
import math
import numpy as np
from PIL import Image
import matplotlib.pyplot as mplot
#List of pixels from data.png
pixels = []
height = 140
width = 200
#Read in data from data.png
data = Image.open( "data.png" )
data = data.convert('RGB')
for row in range(0,height): #loops over the number of rows in the image
for col in range(0,width): # loops over the number of columns in the current row
r,g,b = data.getpixel((row,col))
rgb = []
rgb.append(r)
rgb.append(g)
rgb.append(b)
if rgb != [0,255,0]:
pixels.append(rgb)
但这样做会导致错误:IndexError:图像索引超出范围
我也试过这个:
#Convert to float32 format
data_image = np.float32(data)
#Reads in data points from data.png and appends them to a list
for row in range(len(data_image)): #loops over the number of rows in the image
for col in range(len(data_image[row])): # loops over the number of columns in the current row
pixel = data_image[row][col] #Assigns pixel at row and column to a variable
if pixel != [0,255,0,255]: #If pixel is not green (a.k.a it is a data point)
pixels.append(pixel) #Set key to the location of pixel and set value to pixel color
#Read in data from us_outline.png
img2 = Image.open( "us_outline.png" )
usmap = img2.load()
#Convert to float32 format
usmap_image = np.float32(usmap)
#Writes data from pixels list to US map
for row in range(len(usmap_image)): #loops over the number of rows in the image
for col in range(len(usmap_image[row])): # loops over the number of columns in the current row
for pixel in range(len(pixels)):
if pixels[row][col] == usmap_image[row][col]:
usmap_image[row][col] = pixels[row][col]
usmap_image = np.uint8( usmap_image )
但这样做会导致第21和22行出错
我也试过简单地将两个图像加在一起,但这产生了一个奇怪的结果。
我尝试了很多方法,但我无法弄清楚如何让它发挥作用。请帮忙!
提前致谢
答案 0 :(得分:0)
在您的第一段代码中,您只需要交换row
和col
来正确读取像素。第18行变为
r,g,b = data.getpixel((col, row))
否则,以下代码完成了您的目标,并且更简洁:
import numpy as np
import matplotlib.pyplot as plt
# find indices of non-green pixels
data = plt.imread('data.png')
green = np.zeros_like(data)
green[:,:,1] = 1. # plt.imread for some bizarre reason returns rgb values between 0.-1. for the given pngs, not 0-255!
x, y = np.where(np.any(data != green, axis=-1))
# plot non-green pixels on us outline
us = plt.imread('us_outline.png')
us[x,y] = data[x,y]
plt.imshow(us)
plt.show()