I have converted my image into a csv file and it\'s like a matrix but I want it to be a single row. How can I convert all of the images in dataset into a csv file (each ima
import numpy as np
import cv2
import os
IMG_DIR = '/home/kushal/Documents/opencv_tutorials/image_reading/dataset'
for img in os.listdir(IMG_DIR):
img_array = cv2.imread(os.path.join(IMG_DIR,img), cv2.IMREAD_GRAYSCALE)
img_array = (img_array.flatten())
img_array = img_array.reshape(-1, 1).T
print(img_array)
with open('output.csv', 'ab') as f:
np.savetxt(f, img_array, delimiter=",")
From your question, I think you want to know about numpy.flatten()
. You want to add
value = value.flatten()
right before your np.savetxt call. It will flatten the array to only one dimension and it should then print out as a single line.
The rest of your question is unclear bit it implies you have a directory full of jpeg images and you want a way to read through them all. So first, get a file list:
def createFileList(myDir, format='.jpg'):
fileList = []
print(myDir)
for root, dirs, files in os.walk(myDir, topdown=False):
for name in files:
if name.endswith(format):
fullName = os.path.join(root, name)
fileList.append(fullName)
return fileList
The surround your code with a for fileName in fileList:
Edited to add complete example Note that I've used csv writer and changed your float64 to ints (which should be ok as pixel data is 0-255
from PIL import Image
import numpy as np
import sys
import os
import csv
#Useful function
def createFileList(myDir, format='.jpg'):
fileList = []
print(myDir)
for root, dirs, files in os.walk(myDir, topdown=False):
for name in files:
if name.endswith(format):
fullName = os.path.join(root, name)
fileList.append(fullName)
return fileList
# load the original image
myFileList = createFileList('path/to/directory/')
for file in myFileList:
print(file)
img_file = Image.open(file)
# img_file.show()
# get original image parameters...
width, height = img_file.size
format = img_file.format
mode = img_file.mode
# Make image Greyscale
img_grey = img_file.convert('L')
#img_grey.save('result.png')
#img_grey.show()
# Save Greyscale values
value = np.asarray(img_grey.getdata(), dtype=np.int).reshape((img_grey.size[1], img_grey.size[0]))
value = value.flatten()
print(value)
with open("img_pixels.csv", 'a') as f:
writer = csv.writer(f)
writer.writerow(value)
import os
import pandas as pd
path = 'path-to-the-folder'
os.chdir(path)
lists = os.listdir(path)
labels = []
file_lst = []
for folder in lists:
files = os.listdir(path +"/"+folder)
for file in files:
path_file = path + "/" + folder + "/" + file
file_lst.append(path_file)
labels.append(folder)
dictP_n = {"path": file_lst,
"label_name": labels,
"label": labels}
data = pd.DataFrame(dictP_n, index = None)
data = data.sample(frac=1)
data['label'] = data['label'].replace({"class1": 0, "class2": 1 })
data.to_csv("path-to-save-location//file_name.csv", index =None)
How about you convert your images to 2D numpy arrays and then write them as txt files with .csv extensions and , as delimiters?
Maybe you could use a code like following:
np.savetxt('np.csv', image, delimiter=',')