added project cnn_website

.gitignore

@@ -0,0 +1 @@
+/images/

config/img_config.json

@@ -2,37 +2,52 @@
     "images": [
         {
             "id": "pixelcnn_1",
-            "image": "images/mnist_conditioned_gen_results_cropped.png",
+            "image": "images_jpg/mnist_conditioned_gen_results_cropped.jpg",
             "image_pos": "center"
         },
         {
             "id": "pixelcnn_2",
-            "image": "images/seminararbeit.png",
+            "image": "images_jpg/seminararbeit.jpg",
             "image_pos": "left"
         },
         {
             "id": "boardgame_1",
-            "image": "images/boardgame_demo.png",
+            "image": "images_jpg/boardgame_demo.jpg",
             "image_pos": "center"
         },
         {
             "id": "boardgame_2",
-            "image": "images/boardgame_connection.png",
+            "image": "images_jpg/boardgame_connection.jpg",
             "image_pos": "center"
         },
         {
             "id": "boardgame_3",
-            "image": "images/boardgame_ai.png",
+            "image": "images_jpg/boardgame_ai.jpg",
             "image_pos": "left"
         },
         {
             "id": "towerdefense_1",
-            "image": "images/towerdefense_demo.png",
+            "image": "images_jpg/towerdefense_demo.jpg",
             "image_pos": "center"
         },
         {
             "id": "personal_website_1",
-            "image": "images/personal_website.png",
+            "image": "images_jpg/personal_website.jpg",
+            "image_pos": "left"
+        },
+        {
+            "id": "cnn_website_1",
+            "image": "images_jpg/cnn_website.jpg",
+            "image_pos": "center"
+        },
+        {
+            "id": "cnn_website_2",
+            "image": "images_jpg/cnn_server.jpg",
+            "image_pos": "left"
+        },
+        {
+            "id": "cnn_website_3",
+            "image": "images_jpg/cnn_website_cnn.jpg",
             "image_pos": "left"
         }
     ]

lang/de.json

@@ -8,6 +8,50 @@
   "github_desc": "Auf GitHub ansehen ↗",
   "navbar_group": "Projekte",
   "content": [
+    {
+      "id": "cnn_website",
+      "title": "CNN Website",
+      "description": "Die Website nutzt eine CNN zur spezifizierung von Vogelarten.",
+      "tags": [
+        "React",
+        "PyTorch",
+        "NGINX",
+        "Caddy",
+        "Docker Compose"
+      ],
+      "github": "https://github.com/MarvinKrausser/CNN_Website",
+      "blocks": [
+        {
+          "heading": "Frontend",
+          "text": "Die --link-- ist online. Das Frontend ist mit React umgesetzt und ermöglicht das Hochladen von Bildern sowie die Anzeige der Klassifikationsergebnisse. Es ist responsiv gestaltet und passt sich verschiedenen Bildschirmgrößen an, sodass es auch auf dem Handy gut nutzbar ist.",
+          "image": "cnn_website_1",
+          "links": [
+            {
+              "id": "website",
+              "link": "https://marvinkrausser.com/bird_cnn",
+              "desc": "Website ↗"
+            }
+          ]
+        },
+        {
+          "heading": "Backend",
+          "text": "Das Backend ist containerisiert mit Docker umgesetzt und wird über Docker Compose verwaltet. Caddy fungiert als zentraler Router für alle Anfragen und stellt über Let's Encrypt automatisch SSL-Zertifikate bereit. Die React-Anwendung läuft hinter einem NGINX-Router, während die API als FastAPI-Server implementiert ist. Die --link-- ist über eine Subdomain erreichbar und wird über Caddy an den FastAPI-Server weitergeleitet.",
+          "image": "cnn_website_2",
+          "links": [
+            {
+              "id": "subdomain",
+              "link": "https://api.marvinkrausser.com/docs",
+              "desc": "API ↗"
+            }
+          ]
+        },
+        {
+          "heading": "CNN",
+          "text": "Das CNN klassifiziert 7 Vogelarten aus Bildern. Es verwendet Skip Connections, Dropout und Batch Normalization, um das Training stabiler zu machen und Overfitting zu reduzieren.",
+          "image": "cnn_website_3"
+        }
+      ]
+    },
     {
       "id": "pixelcnn",
       "title": "PixelCNN Bildgeneration",

lang/en.json

@@ -8,6 +8,50 @@
   "github_desc": "View on GitHub ↗",
   "navbar_group": "Projects",
   "content": [
+    {
+      "id": "cnn_website",
+      "title": "CNN Website",
+      "description": "The website uses a CNN for the classification of bird species.",
+      "tags": [
+        "React",
+        "PyTorch",
+        "NGINX",
+        "Caddy",
+        "Docker Compose"
+      ],
+      "github": "https://github.com/MarvinKrausser/CNN_Website",
+      "blocks": [
+        {
+          "heading": "Frontend",
+          "text": "The --link-- is online. The frontend is implemented with React and enables uploading images as well as displaying classification results. It is designed responsively and adapts to different screen sizes, making it easy to use on mobile phones as well.",
+          "image": "cnn_website_1",
+          "links": [
+            {
+              "id": "website",
+              "link": "https://marvinkrausser.com/bird_cnn",
+              "desc": "Website ↗"
+            }
+          ]
+        },
+        {
+          "heading": "Backend",
+          "text": "The backend is implemented in a containerized setup using Docker and is managed via Docker Compose. Caddy acts as a central router for all requests and automatically provides SSL certificates via Let's Encrypt. The React application runs behind an NGINX router, while the API is implemented as a FastAPI server. The --link-- is accessible via a subdomain and is forwarded by Caddy to the FastAPI server.",
+          "image": "cnn_website_2",
+          "links": [
+            {
+              "id": "subdomain",
+              "link": "https://api.marvinkrausser.com/docs",
+              "desc": "API ↗"
+            }
+          ]
+        },
+        {
+          "heading": "CNN",
+          "text": "The CNN classifies 7 bird species from images. It uses skip connections, dropout, and batch normalization to make training more stable and reduce overfitting.",
+          "image": "cnn_website_3"
+        }
+      ]
+    },
     {
       "id": "pixelcnn",
       "title": "PixelCNN Generator",