Skip to main content

A repository for storing my progress of researches.

Project description

Myosotis-Researches

CcGAN (myosotis_researches.CcGAN)

internal

The internal module is used for setting the local package itself, like installing datasets and so on.

Import with code

from myosotis_researches.internal import *
Function Desctiption
install_datasets(datasets_name) Install the datasets in datasets_name to the local python package.
uninstall_datasets() Remove all the datasets installed to the local python package.
show_datasets() Show all datasets installed.

Note:

  1. The path of the installed datasets are

    resources.files("myosotis_researches").join("CcGAN", "<datasets_name>")

    To run this code, remember to add from importlib import resources at the beginning.

utils

The utils module contains some basic functions and classes which are frequently used during the CcGAN research.

Import with code

from myosotis_researches.utils import *
Function Description
concat_image(img_list, gap=2, direction="vertical") Concat images vertically or horizontally.
make_h5(old_datasets_name, size, new_datasets_path, image_indexes, train_indexes, val_indexes) Get piece of original HDF5 datasets.
print_hdf5(name, obj) Print a basic structure of an HDF5 file.

Note:

  1. Function print_hdf5 should be used within a with block:

    import h5py
    
    with h5py.File(<HDF5_file_path>, "r") as f:
      f.visititems(print_hdf5)
    

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

myosotis_researches-0.1.5.tar.gz (62.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

myosotis_researches-0.1.5-py3-none-any.whl (102.6 kB view details)

Uploaded Python 3

File details

Details for the file myosotis_researches-0.1.5.tar.gz.

File metadata

  • Download URL: myosotis_researches-0.1.5.tar.gz
  • Upload date:
  • Size: 62.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for myosotis_researches-0.1.5.tar.gz
Algorithm Hash digest
SHA256 9c1ecd804de4364384f3e0146c69a54d4a9b0865da1592d84ce9f8cbe0279e36
MD5 ad4a6b7b3276c26f03c91b39c5d19a30
BLAKE2b-256 a52671affe46ef6fe6499e7596dd5391b1737575d065eb68f4c239b92ce92798

See more details on using hashes here.

File details

Details for the file myosotis_researches-0.1.5-py3-none-any.whl.

File metadata

File hashes

Hashes for myosotis_researches-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 0a700e81b7c50d52f8a56def58a6968745b6876a73f31823159e383bc7842b81
MD5 0edc834d787541a54d9ba287c6725b4a
BLAKE2b-256 02a716939b911ca3d652c431b22d014f8dff97e86f3e657c3ab625d32608bbf4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page