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  • Photographer/Photon
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Photographer/ Photon

1607runs
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Licence
About this license
CreativeML Open RAIL-MView LICENSE
AddendumView LICENSE

API Sample: Photographer/Photon

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>
      
                        

Tell us about any details you want to generate

Specify things to not see in the output

Your request will cost $0.0006 per second.

(Total cost varies depending on the request’s execution time.)
Photographer-Photon-sample-1.mp4
Photographer-Photon-sample-27.mp4
Photographer-Photon-sample-35.mp4
1744807673 Report This Model

Photon aims to generate photorealistic and visually appealing images effortlessly.

Recommendation for generating the first image with Photon:

  • Prompt: A simple sentence in natural language describing the image.

  • Negative: "cartoon, painting, illustration, (worst quality, low quality, normal quality:2)"

  • Sampler: DPM++ 2M Karras | Steps: 20 | CFG Scale: 6

  • Size: 512x768 or 768x512

  • Hires.fix: R-ESRGAN 4x+ | Steps: 10 | Denoising: 0.45 | Upscale x 2

  • (avoid using negative embeddings unless absolutely necessary)

From this initial point, experiment by adding positive and negative tags and adjusting the settings. Most of the sample images follow this format.

Development

The development process was somewhat chaotic but essentially:

  • It started from an old mix.

  • LORAs were trained on various topics using AI-generated photorealistic images.

  • These LORAs were mixed within the model using different weights.

  • In the midst of this mixing, hand generation broke.

  • LORAs were generated and remixed in an attempt to fix hand generation (not entirely successful).

In future versions, I will try to:

  • Completely eliminate the need for a negative prompt to generate high-quality images.

  • Fix the hand generation issue to minimize instances of poorly drawn hands.

  • Explore more automated training processes. I would love to have 5,000 or 50,000 high-quality AI-generated photorealistic images for training purposes.

I hope you enjoy using it as much as I enjoyed creating it! If you have any questions or suggestions, feel free to share. Have fun creating amazing images! 🎨

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