> For the complete documentation index, see [llms.txt](https://george-jen.gitbook.io/data-science-and-apache-spark/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://george-jen.gitbook.io/data-science-and-apache-spark/image-data-source.md).

# Image Data Source

### Image Data Source

Parquet, CSV, JSON, JDBC and images (JPG and PNG)

This image data source is used to load image files from a directory, it can load compressed image (jpeg, png, etc.) into raw image representation via ImageIO in Java library. The loaded DataFrame has one StructType column: “image”, containing image data stored as image schema. 

### The schema of the image column is:

```
origin: 
StringType (represents the file path of the image)
height: 
IntegerType (height of the image)
width: 
IntegerType (width of the image)
nChannels: 
IntegerType (number of image channels)
mode: 
IntegerType (OpenCV-compatible type)
data: 
BinaryType (Image bytes in OpenCV-compatible order: row-wise BGR in most cases)
```

```
 val df = spark.read.format("image").option("dropInvalid", true).load("/home/dv6/spark/spark/data/mllib/images/origin/kittens")
 df.select("image.origin", "image.width", "image.height").show(truncate=false)
 
 /*
 
 Output:
 
 +-------------------------------------------------------------------------------------+-----+------+
|origin                                                                               |width|height|
+-------------------------------------------------------------------------------------+-----+------+
|file:///home/dv6/spark/spark/data/mllib/images/origin/kittens/54893.jpg              |300  |311   |
|file:///home/dv6/spark/spark/data/mllib/images/origin/kittens/DP802813.jpg           |199  |313   |
|file:///home/dv6/spark/spark/data/mllib/images/origin/kittens/29.5.a_b_EGDP022204.jpg|300  |200   |
|file:///home/dv6/spark/spark/data/mllib/images/origin/kittens/DP153539.jpg           |300  |296   |
+-------------------------------------------------------------------------------------+-----+------+
 
 */
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://george-jen.gitbook.io/data-science-and-apache-spark/image-data-source.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.