问题
I trained a model for Digit Recognizer (https://www.kaggle.com/c/digit-recognizer/data). The input data is a csv file. Each row in the file represent an image which is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. The model is ready to use but I wonder how I can create a testing data for this input? If I have an image with digital number, how can I convert it to 28 by 28 pixels in an array format.
I tried below code but it renders the image background as yellow color. The png image has white background so I don't understand why it shows yellow.
import numpy as np
import cv2
import csv
import matplotlib.pyplot as plt
img = cv2.imread('./test.png', 0) # load grayscale image. Shape (28,28)
flattened = img.flatten() # flatten the image, new shape (784,)
row = flattened.reshape(28,28)
plt.imshow(row)
plt.show()
回答1:
I prepared a little example for you, which gives you hopefully an idea on how you can achieve this task:
I am using this image as example:
Full script:
import numpy as np
import cv2
import csv
img = cv2.imread('./1.png', 0) # load grayscale image. Shape (28,28)
flattened = img.flatten() # flatten the image, new shape (784,)
flattened = np.insert(flattened, 0, 0) # insert the label at the beginning of the array, in this case we add a 0 at the index 0. Shape (785,0)
#create column names
column_names = []
column_names.append("label")
[column_names.append("pixel"+str(x)) for x in range(0, 784)] # shape (785,0)
# write to csv
with open('custom_test.csv', 'w') as file:
writer = csv.writer(file, delimiter=';')
writer.writerows([column_names]) # dump names into csv
writer.writerows([flattened]) # add image row
# optional: add addtional image rows
Now you have the same csv structure as provided in your example.
custom_test.csv output (shortened):
label;pixel0;pixel1;pixel2;pixel3;pixel4;pixel5;pixel6;pixel7;pixel ...
0;0;0;0;0;0;0;0;0;0;0;0....
EDIT: To visualize the flattened image with matplotlib, you have to specfiy a colormap:
row = flattened.reshape(28,28)
plt.imshow(row, cmap='gray') # inverse grayscale is possible with: cmap='gray_r'
来源:https://stackoverflow.com/questions/55898311/how-can-i-convert-a-png-to-a-dataframe-for-python