vizy

Name	vizy JSON
Version	1.0.0 JSON
	download
home_page	None
Summary	Tiny tensor visualiser: vz.plot(t) / vz.save(t)
upload_time	2025-07-11 22:30:17
maintainer	None
docs_url	None
author	Anıl Zeybek
requires_python	>=3.8
license	None
keywords	matplotlib numpy pytorch tensor visualization
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # vizy

**Lightweight tensor visualizer for PyTorch and NumPy**

Display or save any NumPy array or PyTorch tensor with a single line with ease:

```python
import vizy

vizy.plot(tensor)               # shows image or grid
vizy.save("image.png", tensor)  # saves to file
vizy.save(tensor)               # saves to temp file and prints path
vizy.summary(tensor)            # prints info like res, dtype, device, range, etc.
```

Let's say you have a PyTorch `tensor` with shape `(BS, 3, H, W)`. Instead of

```python
plt.imshow(tensor.cpu().numpy()[0].transpose(1, 2, 0))
plt.imshow(tensor.cpu().numpy()[1].transpose(1, 2, 0))
...
```

You can just do:

```python
vizy.plot(tensor)
```

Or if you are in an ssh session, you can just do:

```python
vizy.save(tensor)
```

It will automatically save the tensor to a temporary file and print the path, so you can scp it to your local machine and visualize it.


## Installation

```bash
pip install vizy
```

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "vizy",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.8",
    "maintainer_email": null,
    "keywords": "matplotlib, numpy, pytorch, tensor, visualization",
    "author": "An\u0131l Zeybek",
    "author_email": null,
    "download_url": "https://files.pythonhosted.org/packages/0e/46/49353dfdba71a6939c8e5156d6ea87688a4651d476ab3f2c7227c70618f9/vizy-1.0.0.tar.gz",
    "platform": null,
    "description": "# vizy\n\n**Lightweight tensor visualizer for PyTorch and NumPy**\n\nDisplay or save any NumPy array or PyTorch tensor with a single line with ease:\n\n```python\nimport vizy\n\nvizy.plot(tensor)               # shows image or grid\nvizy.save(\"image.png\", tensor)  # saves to file\nvizy.save(tensor)               # saves to temp file and prints path\nvizy.summary(tensor)            # prints info like res, dtype, device, range, etc.\n```\n\nLet's say you have a PyTorch `tensor` with shape `(BS, 3, H, W)`. Instead of\n\n```python\nplt.imshow(tensor.cpu().numpy()[0].transpose(1, 2, 0))\nplt.imshow(tensor.cpu().numpy()[1].transpose(1, 2, 0))\n...\n```\n\nYou can just do:\n\n```python\nvizy.plot(tensor)\n```\n\nOr if you are in an ssh session, you can just do:\n\n```python\nvizy.save(tensor)\n```\n\nIt will automatically save the tensor to a temporary file and print the path, so you can scp it to your local machine and visualize it.\n\n\n## Installation\n\n```bash\npip install vizy\n```\n",
    "bugtrack_url": null,
    "license": null,
    "summary": "Tiny tensor visualiser: vz.plot(t) / vz.save(t)",
    "version": "1.0.0",
    "project_urls": {
        "Issues": "https://github.com/anilzeybek/vizy/issues",
        "Repository": "https://github.com/anilzeybek/vizy"
    },
    "split_keywords": [
        "matplotlib",
        " numpy",
        " pytorch",
        " tensor",
        " visualization"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "693d5d2084c1fcfddb577c35cc088e31079a9bc3dbf202525b33c7fed13029f1",
                "md5": "77fd11c49712b09dc1be42c82a758ff6",
                "sha256": "4950a26d6ae808810b18580ec0532a0084a2c0299bf079658e1762750e03207b"
            },
            "downloads": -1,
            "filename": "vizy-1.0.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "77fd11c49712b09dc1be42c82a758ff6",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.8",
            "size": 11319,
            "upload_time": "2025-07-11T22:30:16",
            "upload_time_iso_8601": "2025-07-11T22:30:16.571898Z",
            "url": "https://files.pythonhosted.org/packages/69/3d/5d2084c1fcfddb577c35cc088e31079a9bc3dbf202525b33c7fed13029f1/vizy-1.0.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "0e4649353dfdba71a6939c8e5156d6ea87688a4651d476ab3f2c7227c70618f9",
                "md5": "63ff89ae7e59e8cf9011a14ec98fc466",
                "sha256": "9a0124cbc7b5bbbda2a60df2bb7fa0741f7af323a22c443158b52896de3bd277"
            },
            "downloads": -1,
            "filename": "vizy-1.0.0.tar.gz",
            "has_sig": false,
            "md5_digest": "63ff89ae7e59e8cf9011a14ec98fc466",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.8",
            "size": 19170,
            "upload_time": "2025-07-11T22:30:17",
            "upload_time_iso_8601": "2025-07-11T22:30:17.381353Z",
            "url": "https://files.pythonhosted.org/packages/0e/46/49353dfdba71a6939c8e5156d6ea87688a4651d476ab3f2c7227c70618f9/vizy-1.0.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-07-11 22:30:17",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "anilzeybek",
    "github_project": "vizy",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "vizy"
}