| Name | streamlit-overlay JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | Streamlit component that allows you add overlays to images |
| upload_time | 2024-08-05 09:17:24 |
| maintainer | None |
| docs_url | None |
| author | Jens Rahnfeld |
| requires_python | >=3.8 |
| license | None |
| keywords |
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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<div align="center">
<h2>
Streamlit-Overlay 🖼️🖌️
</h2>
<p><b>👌 Simplify adding overlays to images in Streamlit </b></p>
<img src="https://github.com/JensRahnfeld/streamlit-overlay/blob/main/assets/streamlit-overlay.gif">
</div>
## Installation
```
pip install streamlit-overlay
```
## Quick Start
In your `app.py` insert the following lines of code.
```python
from streamlit_overlay import overlay
images = ... # np.narray of shape (#frames, height, width, 3)
masks = ... # np.array of shape (#frames, height, width, 3)
overlay(images, masks, key="example_overlay")
```
Running your app via
```
streamlit run app.py
```
will then render a customizable video demo.
## API
### `streamlit_overlay.overlay(images, masks=[], alpha=0.5, key=None, toggle_label="Display Overlay", fps=30, autoplay=False)`
Creates an instance of the "overlay" component for use in a Streamlit app. It allows for the overlaying of masks on images, with customizable options for transparency, display controls, and playback settings.
<b>Parameters</b>
- `images`: np.ndarray or List[Image]
The images to display. This can be a single image or a sequence of images (for video). The shape should be (height, width, 3) for a single image or (num_frames, height, width, 3) for a sequence.
- `masks`: np.ndarray or List[Image], optional
The masks to overlay on the images. This should match the shape of the images parameter. If not provided, the function will only display the images.
- `alpha`: float, optional
The transparency level for the mask overlay. A value of 0 means the mask is fully transparent, while 1 means it is fully opaque.
- `key`: str or None, optional
An optional key that uniquely identifies this component. If this is
None, and the component's arguments are changed, the component will
be re-mounted in the Streamlit frontend and lose its current state.
- `toggle_label`: str, optional
The label for the toggle button that controls the visibility of the overlay.
- `fps`: int, optional
Frames per second for displaying a video.
- `autoplay`: bool, optional
Whether to automatically start playing the video upon loading. This setting is only relevant if images and masks represent a sequence of frames.
### `streamlit_overlay.heatmap_overlay(images, masks, colormap=cv2.COLORMAP_JET, toggle_label="Display Heatmap", *args, **kwargs)`
Creates an instance of the "heatmap_overlay" component for overlaying heatmaps, e.g. of attribution maps, over images within a Streamlit app. This component processes the provided masks by applying a colormap, enhancing the visualization of data overlays.
<b>Parameters</b>
- `images`: np.ndarray or List[Image]
The images to display. This can be a single image or a sequence of images (for video). The shape should be (height, width, 3) for a single image or (num_frames, height, width, 3) for a sequence.
- `masks`: np.ndarray or List[Image], optional
The masks to overlay on the images. The shape should be (height, width) for a single mask or (num_frames, height, width) for a sequence. These masks will be processed using the specified colormap.
- `colormap`: int, optional
The OpenCV colormap identifier to use for applying color to the masks. This allows for a more vivid and informative visualization of the mask data.
- `toggle_label`: str, optional
The label for the toggle button that controls the visibility of the overlay.
Raw data
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"description": "<div align=\"center\">\r\n <h2>\r\n Streamlit-Overlay \ud83d\uddbc\ufe0f\ud83d\udd8c\ufe0f\r\n </h2>\r\n <p><b>\ud83d\udc4c Simplify adding overlays to images in Streamlit </b></p>\r\n <img src=\"https://github.com/JensRahnfeld/streamlit-overlay/blob/main/assets/streamlit-overlay.gif\">\r\n</div>\r\n\r\n## Installation\r\n\r\n```\r\npip install streamlit-overlay\r\n```\r\n\r\n## Quick Start\r\n\r\nIn your `app.py` insert the following lines of code.\r\n\r\n```python\r\nfrom streamlit_overlay import overlay\r\n\r\nimages = ... # np.narray of shape (#frames, height, width, 3)\r\nmasks = ... # np.array of shape (#frames, height, width, 3)\r\noverlay(images, masks, key=\"example_overlay\")\r\n```\r\n\r\nRunning your app via\r\n\r\n```\r\nstreamlit run app.py\r\n```\r\n\r\nwill then render a customizable video demo.\r\n\r\n## API\r\n\r\n### `streamlit_overlay.overlay(images, masks=[], alpha=0.5, key=None, toggle_label=\"Display Overlay\", fps=30, autoplay=False)`\r\n\r\nCreates an instance of the \"overlay\" component for use in a Streamlit app. It allows for the overlaying of masks on images, with customizable options for transparency, display controls, and playback settings.\r\n\r\n<b>Parameters</b>\r\n\r\n- `images`: np.ndarray or List[Image]\r\n\r\n The images to display. This can be a single image or a sequence of images (for video). The shape should be (height, width, 3) for a single image or (num_frames, height, width, 3) for a sequence.\r\n\r\n- `masks`: np.ndarray or List[Image], optional\r\n\r\n The masks to overlay on the images. This should match the shape of the images parameter. If not provided, the function will only display the images.\r\n\r\n- `alpha`: float, optional\r\n\r\n The transparency level for the mask overlay. A value of 0 means the mask is fully transparent, while 1 means it is fully opaque.\r\n\r\n- `key`: str or None, optional\r\n\r\n An optional key that uniquely identifies this component. If this is\r\n None, and the component's arguments are changed, the component will\r\n be re-mounted in the Streamlit frontend and lose its current state.\r\n\r\n- `toggle_label`: str, optional\r\n\r\n The label for the toggle button that controls the visibility of the overlay.\r\n\r\n- `fps`: int, optional\r\n Frames per second for displaying a video.\r\n\r\n- `autoplay`: bool, optional\r\n\r\n Whether to automatically start playing the video upon loading. This setting is only relevant if images and masks represent a sequence of frames.\r\n\r\n### `streamlit_overlay.heatmap_overlay(images, masks, colormap=cv2.COLORMAP_JET, toggle_label=\"Display Heatmap\", *args, **kwargs)`\r\n\r\nCreates an instance of the \"heatmap_overlay\" component for overlaying heatmaps, e.g. of attribution maps, over images within a Streamlit app. This component processes the provided masks by applying a colormap, enhancing the visualization of data overlays.\r\n\r\n<b>Parameters</b>\r\n\r\n- `images`: np.ndarray or List[Image]\r\n\r\n The images to display. This can be a single image or a sequence of images (for video). The shape should be (height, width, 3) for a single image or (num_frames, height, width, 3) for a sequence.\r\n\r\n- `masks`: np.ndarray or List[Image], optional\r\n\r\n The masks to overlay on the images. The shape should be (height, width) for a single mask or (num_frames, height, width) for a sequence. These masks will be processed using the specified colormap.\r\n\r\n- `colormap`: int, optional\r\n\r\n The OpenCV colormap identifier to use for applying color to the masks. This allows for a more vivid and informative visualization of the mask data.\r\n\r\n- `toggle_label`: str, optional\r\n\r\n The label for the toggle button that controls the visibility of the overlay.\r\n",
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