uppdate

main.py

@@ -115,19 +115,19 @@ async def upload_file(picture: UploadFile):
 
     return JSONResponse(content={'message': 'File successfully uploaded'}, status_code=200)
 
-# @app.get('/get_images', tags=["Predicting"])
-# def get_images():
-#     folder_path = "./static/temporary"
-#     files = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
-#     urls = []
-#     for i in range(0, 3):
-#         url = f'{public_url}/static/temporary/{files[i]}'
-#         urls.append(url)
-#         bentuk, persentase = data_train_pred.prediction(selected_model)
-#     return {'urls': urls, 'bentuk_wajah':bentuk[0], 'persen':persentase}
-
-if __name__ == '__main__':
-    import uvicorn
-    public_url = ngrok.connect(8080).public_url
-    print(f' * Running on {public_url}')
-    uvicorn.run(app, host="0.0.0.0", port=8080)
+@app.get('/get_images', tags=["Predicting"])
+def get_images():
+    folder_path = "./static/temporary"
+    files = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
+    urls = []
+    for i in range(0, 3):
+        url = f'{public_url}/static/temporary/{files[i]}'
+        urls.append(url)
+        bentuk, persentase = data_train_pred.prediction(selected_model)
+    return {'urls': urls, 'bentuk_wajah':bentuk[0], 'persen':persentase}
+
+# if __name__ == '__main__':
+#     import uvicorn
+#     public_url = ngrok.connect(8080).public_url
+#     print(f' * Running on {public_url}')
+#     uvicorn.run(app, host="0.0.0.0", port=8080)