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Remade-AI/ Mona-Lisa

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API Sample: Remade-AI/Mona-Lisa

You don't have any projects yet. To be able to use our api service effectively, please sign in/up and create a project.

Get your api key
  • curl
  • nodejs
  • csharp
  • php
  • swift
  • dart
  • kotlin
  • go
  • python

Prepare Authentication Signature

                          
  //Sign up Wiro dashboard and create project
  export YOUR_API_KEY="{{useSelectedProjectAPIKey}}"; 
  export YOUR_API_SECRET="XXXXXXXXX"; 

   //unix time or any random integer value
  export NONCE=$(date +%s);

  //hmac-SHA256 (YOUR_API_SECRET+Nonce) with YOUR_API_KEY
  export SIGNATURE="$(echo -n "${YOUR_API_SECRET}${NONCE}" | openssl dgst -sha256 -hmac "${YOUR_API_KEY}")";
      
                        

Create a New Folder - Make HTTP Post Request

Create a New Folder - Response

Upload a File to the Folder - Make HTTP Post Request

Upload a File to the Folder - Response

Run Command - Make HTTP Post Request

                          
  curl -X POST "{{apiUrl}}/Run/{{toolSlugOwner}}/{{toolSlugProject}}"  \
  -H "Content-Type: {{contentType}}" \
  -H "x-api-key: ${YOUR_API_KEY}" \
  -H "x-nonce: ${NONCE}" \
  -H "x-signature: ${SIGNATURE}" \
  -d '{{toolParameters}}';

      
                        

Run Command - Response

                          
  //response body
  {
      "errors": [],
      "taskid": "2221",
      "socketaccesstoken": "eDcCm5yyUfIvMFspTwww49OUfgXkQt",
      "result": true
  }
      
                        

Get Task Detail - Make HTTP Post Request

                          
  curl -X POST "{{apiUrl}}/Task/Detail"  \
  -H "Content-Type: {{contentType}}" \
  -H "x-api-key: ${YOUR_API_KEY}" \
  -H "x-nonce: ${NONCE}" \
  -H "x-signature: ${SIGNATURE}" \
  -d '{
    "tasktoken": 'eDcCm5yyUfIvMFspTwww49OUfgXkQt',
  }';

      
                        

Get Task Detail - Response

                          
  //response body
  {
    "total": "1",
    "errors": [],
    "tasklist": [
        {
            "id": "2221",
            "uuid": "15bce51f-442f-4f44-a71d-13c6374a62bd",
            "name": "",
            "socketaccesstoken": "eDcCm5yyUfIvMFspTwww49OUfgXkQt",
            "parameters": {
                "inputImage": "https://api.wiro.ai/v1/File/mCmUXgZLG1FNjjjwmbtPFr2LVJA112/inputImage-6060136.png"
            },
            "debugoutput": "",
            "debugerror": "",
            "starttime": "1734513809",
            "endtime": "1734513813",
            "elapsedseconds": "6.0000",
            "status": "task_postprocess_end",
            "cps": "0.000585000000",
            "totalcost": "0.003510000000",
            "guestid": null,
            "projectid": "699",
            "modelid": "598",
            "description": "",
            "basemodelid": "0",
            "runtype": "model",
            "modelfolderid": "",
            "modelfileid": "",
            "callbackurl": "",
            "marketplaceid": null,
            "createtime": "1734513807",
            "canceltime": "0",
            "assigntime": "1734513807",
            "accepttime": "1734513807",
            "preprocessstarttime": "1734513807",
            "preprocessendtime": "1734513807",
            "postprocessstarttime": "1734513813",
            "postprocessendtime": "1734513814",
            "pexit": "0",
            "categories": "["tool","image-to-image","quick-showcase","compare-landscape"]",
            "outputs": [
                {
                    "id": "6bc392c93856dfce3a7d1b4261e15af3",
                    "name": "0.png",
                    "contenttype": "image/png",
                    "parentid": "6c1833f39da71e6175bf292b18779baf",
                    "uuid": "15bce51f-442f-4f44-a71d-13c6374a62bd",
                    "size": "202472",
                    "addedtime": "1734513812",
                    "modifiedtime": "1734513812",
                    "accesskey": "dFKlMApaSgMeHKsJyaDeKrefcHahUK",
                    "foldercount": "0",
                    "filecount": "0",
                    "ispublic": 0,
                    "expiretime": null,
                    "url": "https://cdn1.wiro.ai/6a6af820-c5050aee-40bd7b83-a2e186c6-7f61f7da-3894e49c-fc0eeb66-9b500fe2/0.png"
                }
            ],
            "size": "202472"
        }
    ],
    "result": true
  }
      
                        

Get Task Process Information and Results with Socket Connection

                          
<script type="text/javascript">
  window.addEventListener('load',function() {
    //Get socketAccessToken from task run response
    var SocketAccessToken = 'eDcCm5yyUfIvMFspTwww49OUfgXkQt';
    WebSocketConnect(SocketAccessToken);
  });

  //Connect socket with connection id and register task socket token
  async function WebSocketConnect(accessTokenFromAPI) {
    if ("WebSocket" in window) {
        var ws = new WebSocket("wss://socket.wiro.ai/v1");
        ws.onopen = function() {  
          //Register task socket token which has been obtained from task run API response
          ws.send('{"type": "task_info", "tasktoken": "' + accessTokenFromAPI + '"}'); 
        };

        ws.onmessage = function (evt) { 
          var msg = evt.data;

          try {
              var debugHtml = document.getElementById('debug');
              debugHtml.innerHTML = debugHtml.innerHTML + "\n" + msg;

              var msgJSON = JSON.parse(msg);
              console.log('msgJSON: ', msgJSON);

              if(msgJSON.type != undefined)
              {
                console.log('msgJSON.target: ',msgJSON.target);
                switch(msgJSON.type) {
                    case 'task_queue':
                      console.log('Your task has been waiting in the queue.');
                    break;
                    case 'task_accept':
                      console.log('Your task has been accepted by the worker.');
                    break;
                    case 'task_preprocess_start':
                      console.log('Your task preprocess has been started.');
                    break;
                    case 'task_preprocess_end':
                      console.log('Your task preprocess has been ended.');
                    break;
                    case 'task_assign':
                      console.log('Your task has been assigned GPU and waiting in the queue.');
                    break;
                    case 'task_start':
                      console.log('Your task has been started.');
                    break;
                    case 'task_output':
                      console.log('Your task has been started and printing output log.');
                      console.log('Log: ', msgJSON.message);
                    break;
                    case 'task_error':
                      console.log('Your task has been started and printing error log.');
                      console.log('Log: ', msgJSON.message);
                    break;
                   case 'task_output_full':
                      console.log('Your task has been completed and printing full output log.');
                    break;
                    case 'task_error_full':
                      console.log('Your task has been completed and printing full error log.');
                    break;
                    case 'task_end':
                      console.log('Your task has been completed.');
                    break;
                    case 'task_postprocess_start':
                      console.log('Your task postprocess has been started.');
                    break;
                    case 'task_postprocess_end':
                      console.log('Your task postprocess has been completed.');
                      console.log('Outputs: ', msgJSON.message);
                      //output files will add ui
                      msgJSON.message.forEach(function(currentValue, index, arr){
                          console.log(currentValue);
                          var filesHtml = document.getElementById('files');
                          filesHtml.innerHTML = filesHtml.innerHTML + '<img src="' + currentValue.url + '" style="height:300px;">'
                      });
                    break;
                }
              }
          } catch (e) {
            console.log('e: ', e);
            console.log('msg: ', msg);
          }
        };

        ws.onclose = function() { 
          alert("Connection is closed..."); 
        };
    } else {              
        alert("WebSocket NOT supported by your Browser!");
    }
  }
</script>
      
                        

Prepare UI Elements Inside Body Tag

                          
  <div id="files"></div>
  <pre id="debug"></pre>
      
                        

Choose an image that will re-generate

Choose an image URL that will re-generate

Trigger Word(s):

Tell us about any details you want to generate

Mona-Lisa scale:

negative prompt

Your request will cost $0.00095 per second.

(Total cost varies depending on the request’s execution time.)
Remade-AI-Mona-Lisa-sample-1.mp4
Remade-AI-Mona-Lisa-sample-2.mp4
1744879798 Report This Model


Mona Lisa Effect LoRA for Wan2.1 14B I2V 480p




Overview


This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to make any person/object in an image become a Mona Lisa version of themselves!





Features



  • Transform any image into a video of the subject as a Mona Lisa version of themselves!

  • Trained on the Wan2.1 14B 480p I2V base model

  • Consistent results across different object types

  • Simple prompt structure that's easy to adapt





Community



  • Discord: Join our community to generate videos with this LoRA for free

  • Request LoRAs: We're training and open-sourcing Wan2.1 LoRAs for free - join our Discord to make requests!






Prompt

The video starts with an image of a woman. The m0n4 Mona Lisa transformation begins as a dark sheet seems to wrap around the woman, and when the image resolves, the woman is depicted as a Mona Lisa version of itself. The Mona Lisa version of the woman sits in a chair with a backdrop featuring a landscape painting.




Prompt

The video starts with an image of a man wearing a suit. The m0n4 Mona Lisa transformation begins as a dark sheet seems to wrap around him, and when the image resolves, he is depicted as a Mona Lisa version of himself. The Mona Lisa version sits in a chair with a backdrop featuring a landscape painting.















Model File and Inference Workflow







📥 Download Links:



  • mona_lisa_45_epochs.safetensors - LoRA Model File

  • wan_I2V_LoRA_workflow.json - Wan I2V with LoRA Workflow for ComfyUI






Recommended Settings



  • LoRA Strength: 1.0

  • Embedded Guidance Scale: 6.0

  • Flow Shift: 5.0





Trigger Words


The key trigger phrase is: m0n4 Mona Lisa transformation





Prompt Template


For best results, try following the structure of the prompt examples above. These worked well for me.





ComfyUI Workflow


This LoRA works with a modified version of Kijai's Wan Video Wrapper workflow. The main modification is adding a Wan LoRA node connected to the base model.


See the Downloads section above for the modified workflow.







Model Information


The model weights are available in Safetensors format. See the Downloads section above.





Training Details



  • Base Model: Wan2.1 14B I2V 480p

  • Training Data: Trained on 35 seconds of video comprised of 7 short clips (each clip captioned separately) of people transforming into Mona Lisa!

  • Epochs: 45





Additional Information


Training was done using Diffusion Pipe for Training





Acknowledgments


Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!



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