Benchmark: Canvas vs img_fixed

HTML Preparation code:

<canvas id="mycanvas" width="256" height="256" style='background: green'></canvas>

<img id="myimage" width="256" height="256" alt='' src='#' style='background: gray'></img>

Script Preparation code:

var i1 = "https://web-dev.imgix.net/image/T4FyVKpzu4WKF1kBNvXepbi08t52/uBEYI93uReLt091i15rF.png?auto=format&w=256"
var i2 = "https://bulma.io/images/placeholders/256x256.png"
var img1 = new Image()
img1.src = i1;

var img2 = new Image()
img2.src = i2;

var canvas = document.getElementById("mycanvas");
var ctx = canvas.getContext('2d');

var img = document.getElementById("myimage");

Tests:

canvas
ctx.drawImage(img1, 0, 0, 256, 256); ctx.drawImage(img2, 0, 0, 256, 256);
img
img.src = i1; img.src = i2

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
canvas
img

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmarking analysis.

**Benchmark Definition and Test Cases**

The provided JSON represents a JavaScript microbenchmark that compares the performance of two approaches: using an HTML `img` element (with fixed size) and drawing directly onto a Canvas element. The test cases are:

1. "canvas": This test case measures the time it takes to draw both images (`i1` and `i2`) onto the canvas using the `drawImage()` method.
2. "img": This test case measures the time it takes to set the source URL of both images (`i1` and `i2`) twice, effectively fetching and displaying them.

**Options Compared**

The two options being compared are:

* Using an HTML `img` element (with fixed size) to display the images
* Drawing directly onto a Canvas element using the `drawImage()` method

**Pros and Cons of Each Approach**

**Canvas Approach:**

Pros:

* Generally faster, as it avoids the overhead of loading multiple images and handling their dimensions.
* Allows for more control over the rendering process.

Cons:

* Requires setting up a canvas element, which can add extra markup and complexity to the HTML.
* May require additional processing if the image needs to be resized or transformed before drawing.

**img Approach:**

Pros:

* Easier to implement, as it only requires setting the `src` attribute of an existing `img` element.
* Already includes the necessary functionality for handling images, such as loading and resizing.

Cons:

* Generally slower, due to the overhead of loading multiple images and processing their dimensions.
* Less control over the rendering process.

**Library and Purpose**

In this benchmark, two libraries are used:

1. `Web Dev Imgix` (not a standard JavaScript library): This is an image hosting service that provides pre-generated, optimized versions of images for web use. In this case, it's used to load the test images (`i1` and `i2`) from a CDN.
2. `Bulma` (not a standard JavaScript library): This is a CSS framework that includes placeholder images for its UI components. In this case, it's used as a reference image (`i2`) with a similar size to the original image.

**Special JS Feature or Syntax**

This benchmark doesn't use any special JavaScript features or syntax beyond the standard `Image` object and the `drawImage()` method.

**Other Alternatives**

If you were to reimplement this benchmark using alternative approaches, some options could be:

* Using SVG elements instead of Canvas or img
* Employing WebAssembly or other low-level optimizations for image processing
* Comparing performance with different image compression algorithms or codecs

Keep in mind that these alternatives would require significant changes to the benchmark and might not provide comparable results.

Related benchmarks:

Canvas vs img_fixed (version: 0)

Comparing performance of: canvas vs img

Created: 3 years ago by: Guest

Jump to the latest result

canvas

img

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):