Free font download site (fonts.google.com)

 go to >> fonts.google.com

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QR detector python code

 refer to code:

.

import cv2

#pip install pyzbar

from pyzbar.pyzbar import decode

def scan_qr_code():

# Start the webcam

cap = cv2.VideoCapture(0)

cap.set(3, 640) # Set the width of the window

cap.set(4, 480) # Set the height of the window

while True:

success, img = cap.read()

if not success:

print("Failed to grab frame")

break

# Decode the QR Code

for barcode in decode(img):

# Get the QR Code position

my_data = barcode.data.decode('utf-8')

pts = barcode.polygon

if len(pts) == 4: # If we have 4 points, then we have a QR code

pts2 = barcode.rect

cv2.putText(img, my_data, (pts2[0], pts2[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 255), 2)

for point in pts:

cv2.circle(img, (point[0], point[1]), 5, (0, 255, 0), cv2.FILLED)

# Display the frame

cv2.imshow('QR Code Scanner', img)

if cv2.waitKey(1) & 0xFF == ord('q'): # Press 'q' to quit

break

cap.release()

cv2.destroyAllWindows()

if __name__ == "__main__":

scan_qr_code()

..

you need to install pyzbar

Thank you.

www.marearts.com

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python code to convert heic (Mac image) to jpeg

 refer to code:

.

# pip install pyheif pillow

# brew install libheif

import os

import subprocess

input_folder = "./input/path"

output_folder = "./output/path"

if not os.path.exists(output_folder):

os.makedirs(output_folder)

for filename in os.listdir(input_folder):

if filename.endswith(".heic") or filename.endswith(".HEIC"):

heic_path = os.path.join(input_folder, filename)

jpeg_path = os.path.join(output_folder, os.path.splitext(filename)[0] + ".jpg")

# Run heif-convert to convert the HEIC file to JPEG

subprocess.run(["heif-convert", heic_path, jpeg_path])

print("Conversion complete!")

..

Thank you.

Download Youtube Video, url to local video file.

The code need to install two YouTube downloader package.

Those are pytube, youtube_dl.

This code try to use one of them because sometime it's fail in certain library.

Enjoy code:

.

import ssl

from pytube import YouTube

import youtube_dl

#pip install pytube

#pip install youtube_dl

def configure_ssl():

try:

_create_unverified_https_context = ssl._create_unverified_context

except AttributeError:

pass

else:

ssl._create_default_https_context = _create_unverified_https_context

def pytube_download(video_url):

try:

yt = YouTube(video_url)

video = yt.streams.get_highest_resolution()

print(f"Downloading: {video.title}")

video.download()

print("Video downloaded successfully using pytube.")

return True

except Exception as e:

print(f"An error occurred while downloading the video with pytube: {e}")

return False

def download_youtube_video(video_url):

download_options = {

'format': 'best',

'outtmpl': '%(title)s-%(id)s.%(ext)s', # Set the output filename format

'progress_hooks': [hook],

}

try:

with youtube_dl.YoutubeDL(download_options) as ydl:

ydl.download([video_url])

print("Video downloaded successfully using youtube-dl.")

except Exception as e:

print(f"An error occurred while downloading the video with youtube-dl: {e}")

def hook(d):

if d['status'] == 'downloading':

print(d['_percent_str'], end="\r")

def main(video_url):

configure_ssl()

if not pytube_download(video_url):

download_youtube_video(video_url)

# Example usage:

if __name__ == "__main__":

video_url = 'https://youtu.be/MareArts' # Add your video url here

main(video_url)

..

Thank you.

www.marearts.com

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3D mesh generation form 3D cloud points, using open3D

 refer to code

.

import open3d as o3d

import numpy as np

import os

def load_point_cloud(file_path):

print("Loading point cloud...")

return o3d.io.read_point_cloud(file_path)

def estimate_normals(pcd):

print("Estimating normals...")

pcd.estimate_normals(search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))

return pcd

def remove_invalid_normals(pcd):

print("Removing invalid normals...")

valid_indices = np.where(np.linalg.norm(np.asarray(pcd.normals), axis=1) != 0)[0]

return pcd.select_by_index(valid_indices)

def poisson_reconstruction(pcd):

print("Performing Poisson surface reconstruction...")

mesh, _ = o3d.geometry.TriangleMesh.create_from_point_cloud_poisson(pcd, depth=8)

return mesh

def simplify_mesh(mesh):

print("Simplifying mesh...")

return mesh.simplify_quadric_decimation(target_number_of_triangles=10000)

def save_mesh(mesh, file_path):

print(f"Mesh saved to '{file_path}'")

o3d.io.write_triangle_mesh(file_path, mesh)

def main():

file_path = "/path/3d_cloud.ply"

pcd = load_point_cloud(file_path)

pcd = estimate_normals(pcd)

pcd = remove_invalid_normals(pcd)

mesh = poisson_reconstruction(pcd)

mesh = simplify_mesh(mesh)

mesh_file = os.path.join(os.path.dirname(file_path), 'mesh.ply')

save_mesh(mesh, mesh_file)

if __name__ == "__main__":

main()

..

install open3d using pip install open3d

Thank you.

www.marearts.com

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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.

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www.marearts.com

convert you opencv camera calibration yaml file to openSFM camera.json file

 refer to code:

.

from PIL import Image

import json

import yaml

import os

import argparse

def get_image_dimensions(image_path):

with Image.open(image_path) as img:

return img.size

def convert_yaml_to_opensfm_json(yaml_file, json_file, image_path):

image_width, image_height = get_image_dimensions(image_path)

with open(yaml_file, 'r') as f:

calibration_data = yaml.safe_load(f)

# Extract the camera matrix and distortion coefficients

camera_matrix = calibration_data['camera_matrix']

dist_coeff = calibration_data['dist_coeff']

# Compute the normalized focal length

focal_normalized = camera_matrix[0][0] / image_width

# Prepare the JSON data

json_data = {

f"custom_camera {image_width} {image_height} perspective 0.0": {

"projection_type": "perspective",

"width": image_width,

"height": image_height,

"focal": focal_normalized,

"k1": dist_coeff[0][0],

"k2": dist_coeff[0][1]

}

}

# Write the JSON data to file

with open(json_file, 'w') as f:

json.dump(json_data, f, indent=4)

def main():

yaml_file="calibration.yaml"

json_file="./camera_models.json"

image_path="IMG_5306.JPG"

convert_yaml_to_opensfm_json(yaml_file, json_file, image_path)

if __name__ == '__main__':

main()

..

reference :

https://github.com/mapillary/OpenSfM/issues/95

https://opensfm.org/docs/geometry.html#camera-models

Thank you.

www.marearts.com

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