jackty9
jackty9
/ nft_python_collage.py
Last active
February 23, 2022 19:01
A collage to join 50 images in a 10 x 5 arrangement.
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| # Import necessary libraries | |
| from PIL import Image | |
| import random | |
| # Connect to Github repo to load images for the collage | |
| !rm -r /content/NFT_tutorial_python | |
| !git clone https://github.com/jackty9/NFT_tutorial_python.git | |
| # Define the size of the collage | |
| collage = Image.new("RGBA", (5000,2500), color=(255,255,255,255)) |
jackty9
/ nft_python_output_generated_images.py
Created
February 17, 2022 23:56
Compose and output generated arts to designated folder
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| # Create a directory for output images | |
| os.mkdir("/content/images/") | |
| # Generate Images | |
| for item in all_images: | |
| im1 = Image.open(f'/content/NFT_tutorial_python/nft_raw_images/backgrounds/{background_files[item["Background"]]}.png').convert('RGBA') | |
| im2 = Image.open(f'/content/NFT_tutorial_python/nft_raw_images/triangles/{triangle_files[item["Triangle"]]}.png').convert('RGBA') | |
| im3 = Image.open(f'/content/NFT_tutorial_python/nft_raw_images/circles/{circle_files[item["Circle"]]}.png').convert('RGBA') | |
| im4 = Image.open(f'/content/NFT_tutorial_python/nft_raw_images/squares/{square_files[item["Square"]]}.png').convert('RGBA') |
jackty9
/ nft_python_define_arts_generation_functions.py
Last active
February 17, 2022 23:31
Define functions to layer traits, generate NFT arts, and assign token IDs
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| # Generate Traits | |
| # Number of random unique images to be generated | |
| TOTAL_IMAGES = 50 | |
| all_images = [] | |
| # A recursive function to generate unique image combinations | |
| def create_new_image(): | |
jackty9
/ nft_python_define_image_traits.py
Last active
February 16, 2022 00:39
Assign the weightages for different traits as well as mapping image file names
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| # Each image is made up a series of traits | |
| # The weitages for each trait distribute the rarity and add up to 100% | |
| background = ["Silver", "Salmon", "Cantaloupe", "Mocha", "Teal"] | |
| background_weights = [40, 30, 15, 10, 5] | |
| triangle = ["Red", "Orange", "Yellow", "Green", "Blue"] | |
| triangle_weights = [40, 30, 15, 10, 5] | |
| circle = ["Red", "Orange", "Yellow", "Green", "Blue"] |
jackty9
/ nft_python_setting_up.py
Last active
July 22, 2022 05:12
Import necessary libraries and cloning Github repo for raw images to generate NFT arts
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| #import necessary libraries | |
| from PIL import Image | |
| import random | |
| import json | |
| import os | |
| #connect to Github repo to load raw images and metadata file | |
| !rm -r /content/NFT_tutorial_python | |
| !git clone https://github.com/jackty9/NFT_tutorial_python.git |
jackty9
/ datetime_python_conditionally_compare.py
Last active
December 13, 2021 21:52
Snippets to conditionally work with datetime
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| #uncomment to import library | |
| #import pandas as pd | |
| #import datetime | |
| #create first datetime dataframe df1 | |
| df1 = pd.DataFrame( | |
| pd.to_datetime(["13:45:33", '14:17:25',"14:13:25", "15:16:43", "16:51:19"]), | |
| columns=["MsgTime"], | |
| ) | |
| print(df1) |
jackty9
/ datetime_python_timezone_calculations.py
Last active
December 12, 2021 22:57
Snippets to work with different time zones
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| #uncomment to import library | |
| #import pandas as pd | |
| #from datetime import datetime | |
| #import pytz, tzlocal | |
| #convert a naive datetime to an aware datetime | |
| dt_naive = pd.to_datetime('2021-11-27T12:24:30') | |
| japan = pytz.timezone("Asia/Tokyo") | |
| dt_aware = dt_naive.tz_localize(japan) | |
| print(dt_aware) |
jackty9
/ datetime_python_string_to_datetime.py
Last active
November 22, 2021 21:58
Snippets to convert strings into datetime format
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| #uncomment to import library | |
| #import pandas as pd | |
| #import datetime as dt | |
| #converting string into datetime | |
| df1 = pd.DataFrame( | |
| { | |
| "DateTime": pd.to_datetime(["2021-11-13 13:45:33", '2021-11-14 14:13:25',"2021-11-15 14:39:25", "2021-11-16 15:16:43", "2021-11-17 16:51:19"]), | |
| } | |
| ) |
jackty9
/ faker_python_export_csv
Created
August 15, 2021 15:59
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| from google.colab import files | |
| customers_df.to_csv('customers_df.csv') | |
| files.download('customers_df.csv') |
jackty9
/ faker_python_generate_fake_data
Last active
August 15, 2021 15:00
Snippets to generate fake data
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| import pandas as pd | |
| import random | |
| from faker import Faker | |
| from random import randrange | |
| from datetime import datetime | |
| nr_of_customers = 1000 | |
| fake = Faker('de_DE') |
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