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# Adjust image opacity
This documentation page is also available as an interactive notebook. You can launch the notebook in
Kaggle or Colab, or download it for use with an IDE or local Jupyter installation, by clicking one of the
above links.
export const quartoRawHtml = [`
| image |
alpha_25 |
alpha_50 |
alpha_75 |
|
|
|
|
`, `
`];
## Problem
You need to make hundreds of images semi-transparent for backgrounds,
overlays, or watermarks.
## Solution
**What’s in this recipe:**
* Set image opacity (transparency level)
* Test transformations before applying
* Apply to multiple images automatically
You adjust image transparency using a custom UDF that modifies alpha
channels (relies on PIL/Pillow). This gives you precise control over
transparency levels.
You can iterate on transformations before adding them to your table. Use
`.select()` with `.collect()` to preview results on sample
images—nothing is stored in your table. If you want to collect only the
first few rows, use `.head(n)` instead of `.collect()`. Once you’re
satisfied, use `.add_computed_column()` to apply the opacity adjustment
to all images in your table.
For more on this workflow, see [Get fast feedback on
transformations](/howto/cookbooks/core/dev-iterative-workflow).
### Setup
```python theme={null}
%pip install -qU pixeltable
```
```python theme={null}
import pixeltable as pxt
from PIL import Image
```
### Load images
```python theme={null}
# Create a fresh directory (drop existing if present)
pxt.drop_dir('image_demo', force=True)
pxt.create_dir('image_demo')
```
Connected to Pixeltable database at: postgresql+psycopg://postgres:@/pixeltable?host=/Users/pjlb/.pixeltable/pgdata
Created directory 'image\_demo'.
\
```python theme={null}
t = pxt.create_table('image_demo/opacity', {'image': pxt.Image})
```
Created table 'opacity'.
```python theme={null}
t.insert(
[
{
'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000776.jpg'
},
{
'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000885.jpg'
},
{
'image': 'https://raw.githubusercontent.com/pixeltable/pixeltable/main/docs/resources/images/000000000016.jpg'
},
]
)
```
Inserting rows into \`opacity\`: 0 rows \[00:00, ? rows/s]Inserting rows into \`opacity\`: 3 rows \[00:00, 545.05 rows/s]
Inserted 3 rows with 0 errors.
3 rows inserted, 6 values computed.
### Iterate: adjust opacity for a few images first
You define a custom function using the `@pxt.udf` decorator to make it
available in Pixeltable. Inside the function, you use standard PIL
(Pillow) operations to manipulate images. Pixeltable handles applying
your function to every row in your table.
**How it works:**
* All image manipulation (`.convert()`, `.split()`, `.point()`,
`.putalpha()`) comes from the PIL/Pillow library
* These are standard Python image operations—see [Pillow
docs](https://pillow.readthedocs.io/) for reference
* The `@pxt.udf` decorator lets Pixeltable apply your function to
table rows
* The opacity parameter (0.0 = fully transparent, 1.0 = fully opaque)
controls the alpha scaling
```python theme={null}
@pxt.udf
def set_opacity(img: Image.Image, opacity: float) -> Image.Image:
"""Set image opacity (0.0 = fully transparent, 1.0 = fully opaque)."""
img = img.convert('RGBA')
alpha = img.split()[3] # Get alpha channel
alpha = alpha.point(lambda p: int(p * opacity)) # Scale alpha values
img.putalpha(alpha)
return img
```
```python theme={null}
# Test 25%, 50%, and 75% opacity
t.select(
t.image,
alpha_25=set_opacity(t.image, 0.25),
alpha_50=set_opacity(t.image, 0.5),
alpha_75=set_opacity(t.image, 0.75),
).head(1)
```
### Add: adjust opacity for all images in your table
```python theme={null}
# Create 50% opacity for backgrounds
t.add_computed_column(semi_transparent=set_opacity(t.image, 0.5))
```
Added 3 column values with 0 errors.
3 rows updated, 3 values computed.
```python theme={null}
# View original and semi-transparent side by side
t.collect()
```
## Explanation
**How the opacity technique works:**
The UDF modifies the alpha channel to control transparency. The function
converts the image to RGBA mode (which includes an alpha channel for
transparency), extracts the alpha channel with `.split()[3]`, scales all
values by the desired opacity factor using
`.point(lambda p: int(p * opacity))`, and applies it back with
`.putalpha()`. This preserves the original image while adjusting only
the transparency level.
**To customize the UDF:**
* **Opacity levels**: Use 0.25 for very faint backgrounds, 0.5 for
standard transparency, 0.75 for subtle effects
* **Selective transparency**: Modify the lambda function in `.point()`
to apply different transparency to different pixel values
* **Preserve regions**: Add conditional logic to keep certain areas
fully opaque
**The Pixeltable workflow:**
In traditional databases, `.select()` just picks which columns to view.
In Pixeltable, `.select()` also lets you compute new transformations on
the fly—define new columns without storing them. This makes `.select()`
perfect for testing transformations before you commit them.
When you use `.select()`, you’re creating a query that doesn’t execute
until you call `.collect()`. You must use `.collect()` to execute the
query and return results—nothing is stored in your table. If you want to
collect only the first few rows, use `.head(n)` instead of `.collect()`
to test on a subset before processing your full dataset. Once satisfied,
use `.add_computed_column()` with the same expression to persist results
permanently.
For more on this workflow, see [Get fast feedback on
transformations](/howto/cookbooks/core/dev-iterative-workflow).
## See also
* [Test transformations with fast feedback
loops](/howto/cookbooks/core/dev-iterative-workflow)
* [Add watermarks to
images](/howto/cookbooks/images/img-add-watermarks)
* [Transform images with PIL
operations](/howto/cookbooks/images/img-pil-transforms)
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