| | <!DOCTYPE html> |
| | <html> |
| | <head> |
| | <meta charset="UTF-8" /> |
| | <meta name="viewport" content="width=device-width, initial-scale=1.0" /> |
| | <script src="https://cdn.tailwindcss.com"></script> |
| | |
| | <script src="https://unpkg.com/es-module-shims@1.7.0/dist/es-module-shims.js"></script> |
| | <script type="importmap"> |
| | { |
| | "imports": { |
| | "@huggingface/inference": "https://cdn.jsdelivr.net/npm/@huggingface/inference@1.8.0/+esm" |
| | } |
| | } |
| | </script> |
| | </head> |
| | <body> |
| | <form class="w-[90%] mx-auto pt-8" onsubmit="launch(); return false;"> |
| | <h1 class="text-3xl font-bold"> |
| | <span |
| | class="bg-clip-text text-transparent bg-gradient-to-r from-pink-500 to-violet-500" |
| | > |
| | Image to text demo with |
| | <a href="https://github.com/huggingface/huggingface.js"> |
| | <kbd>@huggingface/inference</kbd> |
| | </a> |
| | </span> |
| | </h1> |
| |
|
| | <p class="mt-8"> |
| | First, input your token if you have one! Otherwise, you may encounter |
| | rate limiting. You can create a token for free at |
| | <a |
| | target="_blank" |
| | href="https://huggingface.co/settings/tokens" |
| | class="underline text-blue-500" |
| | >hf.co/settings/tokens</a |
| | > |
| | </p> |
| |
|
| | <input |
| | type="text" |
| | id="token" |
| | class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6" |
| | placeholder="token (optional)" |
| | /> |
| |
|
| | <p class="mt-8"> |
| | Pick the model you want to run. Check out over 100 models for image to text |
| | <a |
| | href="https://huggingface.co/tasks/image-to-text" |
| | class="underline text-blue-500" |
| | target="_blank" |
| | > |
| | here</a |
| | >. The default model is for image captioning, but you can do text extraction, ... |
| | </p> |
| |
|
| | |
| | <input |
| | type="text" |
| | id="model" |
| | class="rounded border-2 border-blue-500 shadow-md px-3 py-2 w-96 mt-6" |
| | value="nlpconnect/vit-gpt2-image-captioning" |
| | required |
| | /> |
| |
|
| | <p class="mt-8">Finally the input image</p> |
| |
|
| | <input type="file" required accept="image/*" |
| | class="rounded border-blue-500 shadow-md px-3 py-2 w-96 mt-6 block" |
| | rows="5" |
| | id="prompt" |
| | /> |
| |
|
| | <button |
| | id="submit" |
| | class="my-8 bg-green-500 rounded py-3 px-5 text-white shadow-md disabled:bg-slate-300" |
| | > |
| | Run |
| | </button> |
| |
|
| | <p class="text-gray-400 text-sm">Output logs</p> |
| | <div id="logs" class="bg-gray-100 rounded p-3 mb-8 text-sm"> |
| | Output will be here |
| | </div> |
| |
|
| | </form> |
| |
|
| | <script type="module"> |
| | import { HfInference } from "@huggingface/inference"; |
| | let running = false; |
| | async function launch() { |
| | if (running) { |
| | return; |
| | } |
| | running = true; |
| | try { |
| | const hf = new HfInference( |
| | document.getElementById("token").value.trim() || undefined |
| | ); |
| | const model = document.getElementById("model").value.trim(); |
| | const prompt = document.getElementById("prompt").files[0]; |
| | document.getElementById("logs").textContent = ""; |
| | const {generated_text} = await hf.imageToText({model, data: prompt}); |
| | document.getElementById("logs").textContent = generated_text; |
| | } catch (err) { |
| | alert("Error: " + err.message); |
| | } finally { |
| | running = false; |
| | } |
| | } |
| | window.launch = launch; |
| | </script> |
| | </body> |
| | </html> |
