Autoencoders Let us see how the app interface works by inspecting its functionalities. Here is the main dashboard. A brief description about the project. We clicked "Denoising Dirty Documents" button on the dashboard. Let's upload an image to see the output. The input image is denoised. We can see the clear output. Here is another input and its clear output. We clicked "Reverse Image Search" button on the dashboard. Let's upload an image to see the output. The reverse image search produced 5 similar images as output to "Topwear" input image. The reverse image search produced 5 similar images as output to "Watch" input image. The reverse image search produced 5 similar images as output to "Flipflop" input image. The reverse image search produced 5 similar images as output to "Floater" input image. The reverse image search produced 5 similar images as output to "Shoe" input image. The reverse image search produced 5 similar images as output to "Bottomwear" input image. The reverse image search produced 5 similar images as output to "Socks" input image. The reverse image search produced 5 similar images as output to "Bag" input image. The reverse image search produced 5 similar images as output to "Wallet" input image. We clicked "Semantic Hair Segmentation" button on the dashboard. Let's upload an image to see the output. The output is a predicted binary map and the result applied on actual image. The output is a predicted binary map and the result applied on another actual image.
