Python library for controlling WEOM IR cameras
Project description
WEOM Python interface
version: 1.6.164
WEOMPy is a comprehensive Python library designed to control WEOM cameras using the Python language.
The library can access the following key WEOM thermal core features
- read device information such as serial number, firmware version, etc...
- change display parameters (display palette, contrast, brightness, frame rate, gain, etc..)
- view and capture images
- update thermal core firmware
- manage sensor dead pixels
We provide documentation, howtos and tutorials in a form Jupyter notebooks. The notebooks and example can be found in directory where the library is installed using pip. We strongly recommend the use of Python virtual environments to avoid any possible conflicts. To create and activate a clean WEOMPy Python environment run
⚠️ImportantOn some systems there might be dependency issues using Python installations from Microsoft Store. We strongly discourage from using those.
python -m venv <venv_directories>/weompy
. <venv_directories>/weompy/bin/activate
now we have a clean Python environment and we can proceed by installing the library
pip install weompy
After these steps you can find the documentation and example in
<venv_directories>/weompy/lib/python<version>/site-packages/weompy/example.py
<venv_directories>/weompy/lib/python<version>/site-packages/weompy/user_documentation.ipynb
Also we provide stubs for IDE code completion in
<venv_directories>/weompy/lib/python<version>/site-packages/weompy/weompy.pyi
Prerequisites:
- Python 3.8 - 3.12
- Jupyter extension by Microsoft installed on VSCode, if you want to open user_documentation.ipynb in VSCode
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 Distributions
Built Distributions
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file weompy-1.6.164-cp312-cp312-win_amd64.whl.
File metadata
- Download URL: weompy-1.6.164-cp312-cp312-win_amd64.whl
- Upload date:
- Size: 11.8 MB
- Tags: CPython 3.12, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6ae49ec8ea5c4faa08237d8091450dfca69a94ee9bb0fd307f7de9c97586f059
|
|
| MD5 |
c98b024c0669f13d6358e2c8b6cbd297
|
|
| BLAKE2b-256 |
ec2cc16c0bf67eb9e1fe0d51bb88b0db0d06f99dcc1dcdbe1f016f1a45133899
|
File details
Details for the file weompy-1.6.164-cp312-cp312-manylinux_2_28_x86_64.whl.
File metadata
- Download URL: weompy-1.6.164-cp312-cp312-manylinux_2_28_x86_64.whl
- Upload date:
- Size: 26.6 MB
- Tags: CPython 3.12, manylinux: glibc 2.28+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8803b7673e5e56742d0aaec48f9130c4e33a3520b079e01dd6d512f8e669fdce
|
|
| MD5 |
4dc228443485646534082c34485ddf43
|
|
| BLAKE2b-256 |
f8d8a858ce0a6ebc709408e635b3ecfc26b60eb60d6b338699a5614dcc28137d
|
File details
Details for the file weompy-1.6.164-cp312-cp312-macosx_15_0_arm64.whl.
File metadata
- Download URL: weompy-1.6.164-cp312-cp312-macosx_15_0_arm64.whl
- Upload date:
- Size: 28.0 MB
- Tags: CPython 3.12, macOS 15.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2074b3b53a2797e43fc654a676f640964c41ae6754a3a146a0249fdb56e76146
|
|
| MD5 |
1dea349d0b976d77e71a6c86c3aa9af3
|
|
| BLAKE2b-256 |
ff7fec4d9b409d05ba8cc70d1fc9f86596c77a4c9f15ed1a9d27704a4268a17e
|
File details
Details for the file weompy-1.6.164-cp311-cp311-win_amd64.whl.
File metadata
- Download URL: weompy-1.6.164-cp311-cp311-win_amd64.whl
- Upload date:
- Size: 11.8 MB
- Tags: CPython 3.11, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f16e8e9e4cabf74042f29736db3274d298305a082a5f6075209c0809d62af7c4
|
|
| MD5 |
7db8c8db1c94dbfcd53e420df8641a21
|
|
| BLAKE2b-256 |
4fc7b6287eb2a58f843398cc466a902295e5290831bbae472c3230053b5917f4
|
File details
Details for the file weompy-1.6.164-cp311-cp311-manylinux_2_28_x86_64.whl.
File metadata
- Download URL: weompy-1.6.164-cp311-cp311-manylinux_2_28_x86_64.whl
- Upload date:
- Size: 26.6 MB
- Tags: CPython 3.11, manylinux: glibc 2.28+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
95f47f99bc45b3263828b48548dd8e4effd74800edf724c1c86f8b9e5985c58e
|
|
| MD5 |
f61a79cbe9b55742ed165005466a3aba
|
|
| BLAKE2b-256 |
6e43852f2310375669f2041be00df0bf900c9c9b2e5c400548f95c36187cbba5
|
File details
Details for the file weompy-1.6.164-cp311-cp311-macosx_15_0_arm64.whl.
File metadata
- Download URL: weompy-1.6.164-cp311-cp311-macosx_15_0_arm64.whl
- Upload date:
- Size: 28.0 MB
- Tags: CPython 3.11, macOS 15.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3bea2c073bd0f558546711aabcf116d45a2e75eb8fa167b74a854e55da12111e
|
|
| MD5 |
05788b656a488b28234bc843d13fc326
|
|
| BLAKE2b-256 |
791f7fec4b35126460ce0504e9ce90d2fa8e1ca91d102502e6dfabfc9977a29b
|
File details
Details for the file weompy-1.6.164-cp310-cp310-win_amd64.whl.
File metadata
- Download URL: weompy-1.6.164-cp310-cp310-win_amd64.whl
- Upload date:
- Size: 11.8 MB
- Tags: CPython 3.10, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9b3af408241137a5c3a76b3b573a59143b96a5ad5cc6f7d737c140918d0544a7
|
|
| MD5 |
9c42db763c5c09009e56f36d5ac8a4b3
|
|
| BLAKE2b-256 |
930da1ef762f0764327974694ada7b7f9beb20a1fde4c19f0dc4f450f17bd6e8
|
File details
Details for the file weompy-1.6.164-cp310-cp310-manylinux_2_28_x86_64.whl.
File metadata
- Download URL: weompy-1.6.164-cp310-cp310-manylinux_2_28_x86_64.whl
- Upload date:
- Size: 26.6 MB
- Tags: CPython 3.10, manylinux: glibc 2.28+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c6e3ed2c4c8d51ae7d37db4dcbe15f7155d38a02b4f19c4df6c93c65248d0be7
|
|
| MD5 |
5a8956774f5bd1f79c9d680f72fe5242
|
|
| BLAKE2b-256 |
77b90a1e9179d898e2d61b06e7fae13428feaabb3b0f555f416f02b33cb7baf2
|
File details
Details for the file weompy-1.6.164-cp310-cp310-macosx_15_0_arm64.whl.
File metadata
- Download URL: weompy-1.6.164-cp310-cp310-macosx_15_0_arm64.whl
- Upload date:
- Size: 28.0 MB
- Tags: CPython 3.10, macOS 15.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bc60f978af4ff8aa3b4f7037f5492c38507086d5de38061d5c7f01e75e1b104b
|
|
| MD5 |
5c6fd40ffdff012c588643769f11c60f
|
|
| BLAKE2b-256 |
20d7fd321fa5b0fb54de011067da6b085f03e3ae0cab5229fb2f0b100b4bd619
|
File details
Details for the file weompy-1.6.164-cp39-cp39-win_amd64.whl.
File metadata
- Download URL: weompy-1.6.164-cp39-cp39-win_amd64.whl
- Upload date:
- Size: 11.8 MB
- Tags: CPython 3.9, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
033f53d154fd2f4eeb2615c31ec2100fe8db0868c4700678bee9e261df8b51ef
|
|
| MD5 |
68ead66453a2e46fd43bae6967f28bf0
|
|
| BLAKE2b-256 |
5f3e99debfbb6a0f45eb5fdea836cf11672ccd77a06d31b36a6eb8c04c348686
|
File details
Details for the file weompy-1.6.164-cp39-cp39-manylinux_2_28_x86_64.whl.
File metadata
- Download URL: weompy-1.6.164-cp39-cp39-manylinux_2_28_x86_64.whl
- Upload date:
- Size: 26.6 MB
- Tags: CPython 3.9, manylinux: glibc 2.28+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1e96a2ac932667eee68b1a3d55ac95fb02b254d7fbad137ab3c2f6da16b28f82
|
|
| MD5 |
866c327d5a088e772103460718f99bfa
|
|
| BLAKE2b-256 |
c3dd6c82a7660264173fc0c8f3f2e40871af6d42fd763d801aa4c29c5252b8c5
|
File details
Details for the file weompy-1.6.164-cp39-cp39-macosx_15_0_arm64.whl.
File metadata
- Download URL: weompy-1.6.164-cp39-cp39-macosx_15_0_arm64.whl
- Upload date:
- Size: 28.0 MB
- Tags: CPython 3.9, macOS 15.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
62166986013cdff16478a3a239654c036ad11eacacf111e0c38f8321bc73e9af
|
|
| MD5 |
e88f5026f75aefb5520a0f0b98433eea
|
|
| BLAKE2b-256 |
e3a894a070dec81f1bab7079553b28426a04418d27ec3e76cff29dbbb3192678
|
File details
Details for the file weompy-1.6.164-cp38-cp38-win_amd64.whl.
File metadata
- Download URL: weompy-1.6.164-cp38-cp38-win_amd64.whl
- Upload date:
- Size: 11.8 MB
- Tags: CPython 3.8, Windows x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
55095110fdf92c24309733e811928526fb968a4e0c73ce055e08d567e776053e
|
|
| MD5 |
81036496a8fd92e2763441ee598f5775
|
|
| BLAKE2b-256 |
79e211cf24ac7cdc103f5c760303584c20e5f00888ee0cc85c6154f7c1b01710
|
File details
Details for the file weompy-1.6.164-cp38-cp38-manylinux_2_28_x86_64.whl.
File metadata
- Download URL: weompy-1.6.164-cp38-cp38-manylinux_2_28_x86_64.whl
- Upload date:
- Size: 26.6 MB
- Tags: CPython 3.8, manylinux: glibc 2.28+ x86-64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
595a51a56a1d30fa8f617e0c42fa16e459a7bbdf947e80125846f08f9e88f335
|
|
| MD5 |
e72a901b9866f38adc8056f41e2ebd7f
|
|
| BLAKE2b-256 |
0dfaf46a2270703b925b642a77c11b6b2e82f3c06aff7c4f75f9ee2107af1b35
|
File details
Details for the file weompy-1.6.164-cp38-cp38-macosx_15_0_arm64.whl.
File metadata
- Download URL: weompy-1.6.164-cp38-cp38-macosx_15_0_arm64.whl
- Upload date:
- Size: 28.0 MB
- Tags: CPython 3.8, macOS 15.0+ ARM64
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fe728d640bcc5bd5ecb05b659ddc4fd5535123be9838232b184bd05e6772b3b8
|
|
| MD5 |
537bba2d23e8d9cf28cffcc7ef4a6e97
|
|
| BLAKE2b-256 |
9d1b1e8de6e18350f0bf2f4f1ddd39b103b140e35364c9e3af1ef6a9af491d2c
|