print image exif python code

 refer to code:

.

from PIL import Image, ExifTags

import os

def print_exif_data(directory_path):

"""

Print the EXIF data of every JPEG image in the given directory.

Args:

directory_path (str): Path to the directory containing JPEG images.

"""

# Loop through all files in the directory

for filename in os.listdir(directory_path):

if filename.lower().endswith('.jpg') or filename.lower().endswith('.jpeg'):

filepath = os.path.join(directory_path, filename)

# Open image file

image = Image.open(filepath)

# Extract EXIF data

exif_data = image._getexif()

if exif_data is not None:

# Print EXIF data

print(f"EXIF data for {filename}:")

for tag_id, value in exif_data.items():

tag_name = ExifTags.TAGS.get(tag_id, tag_id)

print(f"{tag_name} ({tag_id}): {value}")

print('-' * 50)

else:

print(f"No EXIF data found for {filename}")

print('-' * 50)

if __name__ == "__main__":

# Define the directory path

directory_path = "/your_path/images"

# Print EXIF data

print_exif_data(directory_path)

..

this is example result 

.

EXIF data for IMG_5602.JPG:

ResolutionUnit (296): 2

ExifOffset (34665): 224

Make (271): Apple

Model (272): iPhone 12 Pro

Software (305): 16.6.1

Orientation (274): 6

DateTime (306): 2023:09:18 16:32:55

YCbCrPositioning (531): 1

XResolution (282): 72.0

YResolution (283): 72.0

HostComputer (316): iPhone 12 Pro

ExifVersion (36864): b'0232'

ComponentsConfiguration (37121): b'\x01\x02\x03\x00'

ShutterSpeedValue (37377): 5.915630897377497

DateTimeOriginal (36867): 2023:09:18 16:32:55

DateTimeDigitized (36868): 2023:09:18 16:32:55

ApertureValue (37378): 1.3561438092556088

BrightnessValue (37379): 2.0295000055765606

ExposureBiasValue (37380): 0.0

MeteringMode (37383): 5

Flash (37385): 16

FocalLength (37386): 4.2

ColorSpace (40961): 65535

ExifImageWidth (40962): 4032

FocalLengthIn35mmFilm (41989): 26

SceneCaptureType (41990): 0

OffsetTime (36880): +03:00

OffsetTimeOriginal (36881): +03:00

OffsetTimeDigitized (36882): +03:00

SubsecTimeOriginal (37521): 447

SubsecTimeDigitized (37522): 447

ExifImageHeight (40963): 3024

SensingMethod (41495): 2

ExposureTime (33434): 0.016666666666666666

FNumber (33437): 1.6

SceneType (41729): b'\x01'

ExposureProgram (34850): 2

ISOSpeedRatings (34855): 160

ExposureMode (41986): 0

FlashPixVersion (40960): b'0100'

WhiteBalance (41987): 0

LensSpecification (42034): (4.2, 4.2, 1.6, 1.6)

LensMake (42035): Apple

LensModel (42036): iPhone 12 Pro back camera 4.2mm f/1.6

MakerNote (37500): b"Apple iOS\x00\x00\x01MM\x00,\x00\x01\x00\t\x00\x00\x00\x0....

..

this is code to update exif

.

from PIL import Image

from PIL.ExifTags import TAGS, TAGS_V2

def update_exif_dimensions(image_path):

# Open the image

img = Image.open(image_path)

# Get EXIF data

exif_data = img._getexif()

# Convert it to a dictionary for easier access

exif_dict = {TAGS.get(k, k): v for k, v in exif_data.items()}

# Update ExifImageWidth and ExifImageHeight with actual dimensions

exif_dict['ExifImageWidth'] = img.width

exif_dict['ExifImageHeight'] = img.height

# Update the EXIF data in the image

img._getexif().update(exif_dict)

# Save the image with updated EXIF data

img.save(image_path)

# Update for a specific image

image_path = "path/to/your/image.jpg" # Replace with the actual path to your image

update_exif_dimensions(image_path)

..

Thank you.

🙇🏻‍♂️

www.marearts.com

download ttf font file

 download ttf font file: https://github.com/MareArts/font_ttf

Font Name
Arial
Arial Bold
Arial Bold Italic
Arial Italic
Courier New
Verdana
Verdana Bold
Verdana Bold Italic
Verdana Italic

www.marearts.com

Thank you.

🙇🏻‍♂️

Drawing rectangle and text on image using cv2, pillow (python code)

 Draw text & rectangle on image

Ver.1 pillow

.

from PIL import Image, ImageDraw, ImageFont

import json

# Display the image in Jupyter Notebook

from IPython.display import display

def draw_rect_text(base_dir, json_fn):

# Load JSON file

with open(base_dir+json_fn, 'r') as f:

data = json.load(f)

# Load image

img = Image.open(base_dir+data['image_file_name']+'.jpg')

# Create a draw object

draw = ImageDraw.Draw(img)

# Loop through OCR data and draw rectangles and text

for ocr in data['ocr']:

left = ocr['left']

top = ocr['top']

right = ocr['right']

bottom = ocr['bottom']

text = ocr['text']

# Draw rectangle

draw.rectangle((left, top, right, bottom), outline=(255, 0, 0), width=2)

# Draw text

font = ImageFont.truetype('arial.ttf', size=14)

text_size = draw.textsize(text, font=font)

text_x = left

text_y = top - text_size[1]

draw.text((text_x, text_y), text, font=font, fill=(255, 0, 0))

# Display image

# img.show() #now window

display(img) #display on notebook

..

Ver .2 cv2

.

import cv2

import json

def draw_rect_text(base_dir, json_fn):

# Load JSON file

with open(base_dir+json_fn, 'r') as f:

data = json.load(f)

print(base_dir+data['image_file_name']+'.jpg')

# Load image

img = cv2.imread(base_dir+data['image_file_name']+'.jpg')

# Loop through OCR data and draw rectangles and text

for ocr in data['ocr']:

left = ocr['left']

top = ocr['top']

right = ocr['right']

bottom = ocr['bottom']

text = ocr['text']

# Draw rectangle

cv2.rectangle(img, (left, top), (right, bottom), (0, 0, 255), 2)

# Draw text

font = cv2.FONT_HERSHEY_SIMPLEX

font_scale = 0.5

thickness = 1

text_size = cv2.getTextSize(text, font, font_scale, thickness)[0]

text_x = left

text_y = top - text_size[1]

cv2.putText(img, text, (text_x, text_y), font, font_scale, (0, 0, 255), thickness)

# Display image

cv2.imshow('Image', img)

cv2.waitKey(0)

cv2.destroyAllWindows()

..

Thank you.

🙇🏻‍♂️

www.marearts.com

PIL image to tensor

 refer to code

key is "transforms.PILToTensor"

..

import torch

from PIL import Image

import torchvision.transforms as transforms

pil_image = Image.open('input.jpg')

transform = transforms.Compose([

transforms.PILToTensor()

])

tensor_img = transform(pil_image)

print(tensor_img)

..

Thx. 🙇🏻‍♂️

check image is single color or not, python , PIL image

 refer to example code

..

#get image data

image = Image.open(xxx)

image = image.convert('RGB')

#skip if image has one color

colors = image.getcolors(image.size[0]*image.size[1])

imgH = image.size[1]

imgW = image.size[0]

#print(f'img object w:{imgW}, h:{imgH}')

if len(colors) == 1:

continue

..

www.marearts.com

Thank you.

🙇🏻‍♂️

python pil change dpi without save file

 

look at the code! ^^

..

#load image

tif_path = './input_img.tif'

#open image

pil_image = Image.open(tif_path)

#change dpi in memory

temp_mem_file = BytesIO()

page.save(temp_mem_file, format='png', dpi=(100,100))

#save it to pil

temp_mem_file.seek(0)

pil_image = Image.open(temp_mem_file)

#do it someting

#..

#save file

pil_image.save('./output.png')

#www.marearts.com

#study.marearts.com

..

Thank you.

No module named 'PIL'

pip install --upgrade pip

 pip install pillow

PIL to string, string to PIL (python)

It's simple example source code for that:

PIL to string(base64)
- PIL open image
- image to byte
- byte to string (base64)

string(base64) to PIL
- string to byte
- PIL load byte

--

import base64
import io
from PIL import Image

#open file using PIL
pil_img = Image.open('IMG_0510.jpg')
width, height = pil_img.size
print(width, height)


#get image data as byte
buffer = io.BytesIO()
pil_img.save(buffer, format=pil_img.format)
buffer_value = buffer.getvalue()

#byte to string
base64_str = base64.b64encode(buffer_value)

#read string to image buffer
buffer2 = base64.b64decode(base64_str)
pil_img2 = Image.open(io.BytesIO(buffer2))
width2, height2 = pil_img2.size
print(width2, height2)


#check first & second image
pil_img.show()
pil_img2.show()

--

here, another source code for :
OpenCV -> PIL -> resize -> OpenCV

http://study.marearts.com/2019/06/opencv-pil-resize-opencv.html

OpenCV -> PIL -> resize -> OpenCV

Some simple code for this processing

1. Read image by OpenCV
2. Conver from OpenCV to PIL image
3. some processing using PIL, ex)resize
4. Conver from PIL to OpenCV

Check this code.

import cv2
from PIL import Image
import numpy

#target resize
r_x = 100
r_y = 100


#read image using opencv
cv_img_o = cv2.imread('A.png')

#conver mat to pil
cv_img = cv2.cvtColor(cv_img_o, cv2.COLOR_BGR2RGB)
im_pil = Image.fromarray(cv_img)

#resize pil
im_pil = im_pil.resize((r_x,r_y), Image.ANTIALIAS)

#convert pil to mat
cv_img_r = numpy.array(im_pil)

# Convert RGB to BGR
cv_img_r = cv2.cvtColor(cv_img_r, cv2.COLOR_RGB2BGR)
#cv_img_r = cv_img_r[:, :, ::-1].copy()

cv2.namedWindow('origin',0)
cv2.imshow('origin', cv_img_o)

cv2.namedWindow('resize',0)
cv2.imshow('resize', cv_img_r)

cv2.waitKey(0)