Properties with high-quality images on the listing sell faster and bring more income.
Studies show that fixing different aspects of the listing's image, such as brightness, color balance and clarity, helps increase demand for the property.
Zhang, Shunyuan (2019): A Structural Analysis of Sharing Economy Leveraging Location and Image Analytics Using Deep Learning. Carnegie Mellon University. *Based on analysis of over 510,000 AirBnB pictures
With better images, your agents, hosts and owners will sell faster and earn more. And your buyers will get a more satisfying visual experience from using your platform.
Real estate websites often get photos directly from agents and home owners. Unfortunately, non-professional photographers lack the equipment and skills to produce high-quality photos.
Organizing photoshoots is one way to improve the quality of visuals. But it increases costs and time-to-market.
Another option is automated image editing. It cannot completely replace professional photoshoots. But it can do the bulk of the job in a fraction of a time — especially if it's powered by AI trained on large datasets.
For best results, you should make property photos bright, vibrant and clear. And this is exactly what Claid does.
With Claid, you can:
- Make images clear and sharp by increasing their resolution to your requirements. Eg, Zillow recommends using the 2048 x 1536 size.
- Clean up photos from noise and compression artifacts
- Fix colors, lighting and white balance with content-aware HDR filter that adapts to each photo
- Enhance 360-photos for seamless stitching
- Optimize images for fast page loading by converting them to modern formats, such as progressive JPEG, WebP and AVIF
Most of these features are powered by machine learning. This means, they are on par with manual editing and in some cases, such as lossless upscaling, simply don’t have alternatives.
Interior photos taken without lighting equipment are often dark and pale. Exterior images have the opposite problem: a lot of them are too bright and overlit. Claid fixes both of these problems. It applies intelligent HDR filter based on the content of each photo.
3D property tours became a must for real estate websites. Claid API enables you to enhance panoramic photos without worrying about inconsistent stitching that often occurs when editing 360 pictures.
Image editing can change things to the point when they almost no longer represent reality. That's why many real estate platforms forbid over-processing. Claid enhances photos without changing their content. So you don't have to worry about misleading your customers due to excessive image manipulations.
Drone photography is a great way to showcase the location of a property. By upscaling such photos with AI you'll enable your users to zoom in and inspect images in greater detail.
When photos come from different sources they vary not only in quality but also in the editing style. Claid allows you to process images in a uniform manner and secure a consistent style of imagery across your platform.
Claid API supports stacking up different operations to make every photo meet your requirements in a single call. In the next section, you'll learn how to do it.
Check out how Claid API can enhance images to meet the standards of your real estate site or mobile app.
Below, you can see an example of a virtual property tour photo taken without professional equipment (top) and the same photo processed with Claid API (bottom).
Original 360 image (1920 x 960)
360 image processed with Claid API (2880 x 1440)
And following is a Claid API request which produces this result. Below, we explain the options used to get this result. Please visit Image Processing API for a full reference on Claid API parameters.
curl -X POST --location "https://api.claid.ai/v1-beta1/image/edit" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR-API-KEY" \
restorationsallows choosing from a wide range of neural networks to decompress and upscale images. Here, we went with "photo" as an upscaling mode. This network works well with pictures taken with phones and digital cameras alike. Go to Restorations section to learn more about how Claid can restore image quality.
resizingblock describes the image size. It can define the exact resolution or an upscaling factor according to the platform guidelines. In our case, we specify that we want to increase image resolution by 150% or 1.5 times, which is a popular choice among our real estate clients. See Resizing section to learn about this and other supported options.
adjustmentsspecifies color adjustments applied to an image. Here, we have an ML-powered hdr algorithm applied with 100% intensity which intelligently tunes colors and shadows.
stitching: truemeans that virtual tour photos will be processed to achieve seamless stitching after enhancement. Color Adjustments section describes this in detail.
outputblock states that we want to create a JPEG with a quality of 85. In the API response, we will receive a temporary URL of a resulting image. Please consult Image I/O for an explanation of this block, and Storages section if you want to connect Claid API directly with your Cloud Storage in a secure way.