Supported Transformations
At PixelBin.io, we offer a diverse range of image transformations that seamlessly integrate into Zapier automation. When setting up a Zap action to transform images using PixelBin.io, you specify a transformation string. For instance, to remove backgrounds, you can use methods like erase.bg(). You can further customize these transformations with additional configurations and parameters. For example, erase.bg(i:ecommerce, shadow:true, r:true) allows you to specify parameters such as including ecommerce-related considerations, adding shadows, and applying additional refinements.
You can take a look at our tutorial here.
You are also able to apply multiple transformations with a single transformation string using the ~ symbol. We call it chained transformations. For example: erase.bg()~t.trim(t:46). Learn more about chained transformations here.
Available Methods and Configurations
- ML Transformations
- Basic Transformations
| Name | Description | Example |
| Artifact Removal | Remove JPEG compression artifact noise and get cleaner images | af.remove() |
| AI Background Generator | Generate a background for images using AI. You need add prompt using `p` in base64 string | generate.bg(p:YmVhY2g,f:Background,s:236) |
| AI Variation Generator | Generate variations of an input image based on an optional prompt condition. | vg.generate(v:2,s:70,auto:false) |
| Erase BG | Remove the background of any image | erase.bg() |
| Intelligent Crop | Use this transformation to Intelligently Crop your images | ic.crop(obj:bear) |
| AI Shadow Generator | Generate shadows for objects in your images using AI | shadow.gen(bgc:219653,a:109.6,i:0.6) |
| Upscale | Upscale your images to a larger resolution | sr.upscale(t:4x,enhance_face:true,) |
| Watermark Remover | Produce watermark free images | wm.remove() |
| Name | Description | Example |
| Resize | Resize your images by setting the width and/or height parameters, using different crop parameters like cover, fill, etc. | t.resize(h:416,w:424,) |
| Compress | Compress any image to the desired size | t.compress(q:67) |
| Extend | Extends/pads the edges of the image with the provided background colour. This operation will always occur after resizing and extraction if any. | t.extend(t:124,l:88,b:80,r:69,dpr:1.8) |
| Extract | Extract a region by setting parameters like top, height, width, etc. | ocr.extract() |
| Trim | Trim "boring" pixels from all edges that contain values similar to the top-left pixel. Images consisting entirely of a single colour will calculate "boring" using the alpha channel if any. | t.trim(t:124) |
| Rotate | Rotate the image by setting the angle parameter | t.rotate(a:71) |
| Flip | Mirror the image vertically | t.flip() |
| Flop | Mirror the image horizontally | t.flop() |
| Sharpen | Sharpen an image | t.sharpen(s:3.5) |
| Median | Apply a Median Filter to reduce impulsive, or salt-and-pepper noise | t.median(s:4) |
| Blur | Apply blur effect on your image. Use the sigma parameter to apply an accurate Gaussian Blur | t.blur(s:18.4) |
| Flatten | Merge alpha transparency channel, if any, with a background, then remove the alpha channel | t.flatten(b:219653) |
| Negative | Creates the negative of the image | t.negate() |
| Normalize | Color Normalise Image | t.normalise() |
| Levels | Apply the linear formula a * input + b to the image | t.linear(a:8,b:8) |
| Modulate | Transform the image using brightness, saturation, hue rotation, and lightness. Brightness and lightness both operate on luminance, with the difference being that brightness is multiplicative whereas lightness is additive. | t.modulate(b:2.9,s:4.2,h:-14) |
| Greyscale | Change image contrast to black-and-white or grey monochrome | t.grey() |
| Tint | Increase the lightness of colours in the image | t.tint(c:219653) |
| Change Format | Change image to a different format | t.toFormat(f:png) |
| Change DPI | Change the DPI of an image | t.density(d:263) |
| Merge | Overlay or underlay an image over the another one | t.merge(m:underlay,bg:219653,h:5653,w:5217,t:2809) |