python - Convert image files to a csv file

Python - Convert image files to a csv file

To convert image files to a CSV file, you can use a library like Pandas along with PIL (Python Imaging Library) or its successor Pillow for working with images. The idea is to read each image, convert its pixel values into a flat list, and then store that list along with the image metadata in a CSV file.

Here's a basic example using Pandas and Pillow:

import os from PIL import Image import pandas as pd def image_to_list(image_path): # Open the image img = Image.open(image_path) # Convert the image to grayscale (optional, depending on your use case) img = img.convert('L') # Flatten the pixel values into a list pixel_values = list(img.getdata()) return pixel_values def images_to_csv(input_folder, output_csv): # Get a list of image file names in the input folder image_files = [f for f in os.listdir(input_folder) if f.endswith(('.jpg', '.jpeg', '.png'))] # Create an empty DataFrame df = pd.DataFrame() # Iterate through each image file for image_file in image_files: image_path = os.path.join(input_folder, image_file) # Get pixel values as a list pixel_values = image_to_list(image_path) # Create a row in the DataFrame with the image file name and pixel values df = pd.concat([df, pd.DataFrame({'Image': [image_file], 'Pixel_Values': [pixel_values]})], ignore_index=True) # Save the DataFrame to a CSV file df.to_csv(output_csv, index=False) # Example usage input_folder = '/path/to/images' output_csv = 'images_data.csv' images_to_csv(input_folder, output_csv)

Make sure to replace '/path/to/images' with the path to your folder containing image files. This example assumes the images are in grayscale, and the pixel values are flattened into a single list. Adjust the code based on your specific image data and requirements.

Examples

  1. "Convert a directory of images to a CSV file with image paths"

    • Code:
      import os import csv image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg') or filename.endswith('.png'): image_path = os.path.join(image_directory, filename) writer.writerow({'image_path': image_path})
    • Description: Lists image files in a directory and writes their paths to a CSV file.

  2. "Convert image files to CSV with additional metadata (width, height)"

    • Code:
      from PIL import Image import os import csv image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path', 'width', 'height'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg') or filename.endswith('.png'): image_path = os.path.join(image_directory, filename) img = Image.open(image_path) width, height = img.size writer.writerow({'image_path': image_path, 'width': width, 'height': height})
    • Description: Adds image width and height metadata to the CSV file along with image paths.

  3. "Convert images in a specific format to CSV with file names and sizes"

    • Code:
      import os import csv image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_name', 'file_size'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg'): image_name = os.path.splitext(filename)[0] image_path = os.path.join(image_directory, filename) file_size = os.path.getsize(image_path) writer.writerow({'image_name': image_name, 'file_size': file_size})
    • Description: Converts only JPEG images to a CSV file with image names and file sizes.

  4. "Convert images to CSV with additional information using a custom function"

    • Code:
      from PIL import Image import os import csv def get_image_info(image_path): img = Image.open(image_path) width, height = img.size return {'image_path': image_path, 'width': width, 'height': height} image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path', 'width', 'height'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.png'): image_path = os.path.join(image_directory, filename) info = get_image_info(image_path) writer.writerow(info)
    • Description: Utilizes a custom function to gather additional information about images and writes to the CSV file.

  5. "Convert images to CSV with color histograms"

    • Code:
      from PIL import Image import os import csv import numpy as np def get_color_histogram(image_path): img = Image.open(image_path) histogram = np.histogram(np.array(img).flatten(), bins=256, range=[0, 256])[0] return histogram.tolist() image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path'] + [f'bin_{i}' for i in range(256)] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg'): image_path = os.path.join(image_directory, filename) histogram = get_color_histogram(image_path) writer.writerow({'image_path': image_path, **{f'bin_{i}': count for i, count in enumerate(histogram)}})
    • Description: Computes color histograms for images and writes the data to a CSV file.

  6. "Convert images to CSV with image metadata and pixel values"

    • Code:
      from PIL import Image import os import csv import numpy as np image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path', 'width', 'height', 'pixel_values'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.png'): image_path = os.path.join(image_directory, filename) img = Image.open(image_path) width, height = img.size pixel_values = np.array(img).flatten().tolist() writer.writerow({'image_path': image_path, 'width': width, 'height': height, 'pixel_values': pixel_values})
    • Description: Writes image metadata (width, height) and pixel values to a CSV file.

  7. "Convert images to CSV with image names and dominant colors"

    • Code:
      from PIL import Image import os import csv import colorgram def get_dominant_colors(image_path, num_colors=3): img = Image.open(image_path) colors = colorgram.extract(img, num_colors) return [tuple(color.rgb) for color in colors] image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_name', 'dominant_color_1', 'dominant_color_2', 'dominant_color_3'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg'): image_name = os.path.splitext(filename)[0] image_path = os.path.join(image_directory, filename) colors = get_dominant_colors(image_path) writer.writerow({'image_name': image_name, **{f'dominant_color_{i+1}': color for i, color in enumerate(colors)}})
    • Description: Extracts dominant colors from images and writes to a CSV file along with image names.

  8. "Convert images to CSV with basic EXIF data"

    • Code:
      from PIL import Image from PIL.ExifTags import TAGS import os import csv def get_exif_data(image_path): img = Image.open(image_path) exif_data = img._getexif() return {TAGS[key]: exif_data[key] for key in exif_data if key in TAGS and isinstance(exif_data[key], (str, int, bytes))} image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path'] + [TAGS[key] for key in TAGS if isinstance(key, int)] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.jpg'): image_path = os.path.join(image_directory, filename) exif_data = get_exif_data(image_path) writer.writerow({'image_path': image_path, **exif_data})
    • Description: Retrieves basic EXIF data from images and writes to a CSV file.

  9. "Convert images to CSV with custom image features"

    • Code:
      from skimage import io, color, feature import os import csv def custom_image_features(image_path): img = io.imread(image_path) gray_img = color.rgb2gray(img) edges = feature.canny(gray_img) return {'image_path': image_path, 'edge_count': np.sum(edges)} image_directory = '/path/to/images' csv_file = 'image_data.csv' with open(csv_file, 'w', newline='') as csvfile: fieldnames = ['image_path', 'edge_count'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for filename in os.listdir(image_directory): if filename.endswith('.png'): image_path = os.path.join(image_directory, filename) features = custom_image_features(image_path) writer.writerow(features)
    • Description: Computes custom image features (edge count) and writes to a CSV file.

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