Update lib/enchance.js

lib/enchance.js

@@ -1,87 +1,50 @@
-import WebSocket from "ws"
 import Jimp from "jimp"
 import FormData from "form-data"
 import axios from "axios"
 
-async function upscaler(images) {
-  return new Promise((resolve, reject) => {
-    const ws = new WebSocket("wss://sczhou-codeformer.hf.space/queue/join");
-    const session_hash = Math.random().toString(36).substring(2).slice(1);
-    
-    ws.on("open", () => {
-        console.log("new client upscaler")
-    })
-
-    ws.on("message", (message) => {
-      try {
-        const msg = JSON.parse(message)
-        if(msg.msg == "send_hash") {
-            ws.send(JSON.stringify({ fn_index: 0, session_hash }));
-        } else if(msg.msg == "send_data") {
-            ws.send(JSON.stringify({
-                data: [
-                    images,
-                    true,
-                    true,
-                    true,
-                    3,
-                    0.5
-                ],
-                event_data: null,
-                fn_index: 0,
-                session_hash
-            }));
-        } else if(msg.msg == "estimation") {
-          console.log("Progress: " + msg.rank);
-        } else if(msg.msg == "process_completed") {
-            resolve(msg.output);
-        };
-
-      } catch(e) {
-          reject(e.message);
-      } finally {
-        ws.closeAllListener();
-        ws.close();
-      }
-    })
-
-    ws.on("error", (err) => {
-        return err;
-    });
-  })
-
-}
-
 async function processImageUpscaler({ buffer, method, filenames, mimetype }) {
-  return new Promise(async (resolve, reject) => {
-    let Methods = ["enhance"];
-    Methods.includes(method)? (method = method) : (method = Methods[0]);
-
-    let buffer,
-        formData = new FormData(),
-        scheme = "https://" + "inferenceengine" + ".vyro" + ".ai/" + method;
-
-    formData.append("model_version", 1);
-
-    formData.append("image", Buffer.from(buffer), {
-      filename: filenames,
-      contentType: mimetype,
+    return new Promise(async (resolve, reject) => {
+        let Methods = ["enhance"];
+        Methods.includes(method) ? (method = method) : (method = Methods[0]);
+
+        let buffer,
+            Form = new FormData(),
+            scheme = "https" + "://" + "inferenceengine" + ".vyro" + ".ai/" + method;
+
+        Form.append("model_version", 1);
+
+        Form.append("image", buffer, {
+            filename: filenames,
+            contentType: mimetype,
+        });
+
+        Form.submit({
+                url: scheme,
+                host: "inferenceengine" + ".vyro" + ".ai",
+                path: "/" + method,
+                protocol: "https:",
+                headers: {
+                    "User-Agent": "okhttp/4.9.3",
+                    Connection: "Keep-Alive",
+                    "Accept-Encoding": "gzip",
+                },
+            },
+            function(err, res) {
+                if (err) reject(err);
+                let data = [];
+                res
+                    .on("data", function(chunk) {
+                        data.push(chunk);
+                    })
+                    .on("end", () => {
+                        resolve(Buffer.concat(data));
+                    });
+                res.on("error", (e) => {
+                    reject(e);
+                });
+            }
+        );
     });
+};
 
-    const headers = {
-      "User-Agent": "okhttp/4.9.3",
-      Connection: "Keep-Alive",
-      "Accept-Encoding": "gzip",
-    };
-
-    axios.post(scheme, formData, { headers })
-     .then(response => {
-        resolve(response.data);
-      })
-     .catch(error => {
-        reject(error);
-      });
-  });
-}
-
-export { upscaler, processImageUpscaler }
+export { processImageUpscaler }