Jpg to csv python

Converting images to csv file in python

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=',') 

From your question, I think you want to know about numpy.flatten() . You want to add

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 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=",") 

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Jpg to csv python

Projects and Applications with NumPy

Introduction

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NumPy and Random Data

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Universal Functions

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Python Convert Image (JPG, PNG) to CSV

Given an image as a .png or .jpeg file. How to convert it to a CSV file in Python?

Convert the image to a CSV using the following steps:

1. Read the image into a PIL.Image object.
2. Convert the PIL.Image object to a 3D NumPy array with the dimensions rows, columns, and RGB values.
3. Convert the 3D NumPy array to a 2D list of lists by collapsing the RGB values into a single value (e.g., a string representation).
4. Write the 2D list of lists to a CSV using normal file I/O in Python.

Here’s the code that applies these four steps, assuming the image is stored in a file named ‘c++.jpg’ :

from PIL import Image import numpy as np # 1. Read image img = Image.open('c++.jpg') # 2. Convert image to NumPy array arr = np.asarray(img) print(arr.shape) # (771, 771, 3) # 3. Convert 3D array to 2D list of lists lst = [] for row in arr: tmp = [] for col in row: tmp.append(str(col)) lst.append(tmp) # 4. Save list of lists to CSV with open('my_file.csv', 'w') as f: for row in lst: f.write(','.join(row) + '\n')

Note that the resulting CSV file looks like this with super long rows.

Each CSV cell (column) value is a representation of the RGB value at that specific pixel. For example, [255 255 255] represents the color white at that pixel.

For more information and some background on file I/O, check out our detailed tutorial on converting a list of lists to a CSV:

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