Resolve merge conflict in README.md and finalize project setup

.gitattributes

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README.md

@@ -1,21 +1,30 @@
+---
+title: CV InsectClassifier # Ini dari bagian remote, kamu bisa ubah namanya jadi lebih deskriptif kalau mau
+emoji: 🐞 # Kamu bisa pilih emoji yang kamu suka, misal tetap 🐞
+colorFrom: gray
+colorTo: green
+sdk: docker
+pinned: false
+---
+
 # 🐞 Insect Classifier - FastAPI
 
 A web-based insect classification app using two TensorFlow models (CNN and MobileNet), deployed with FastAPI. Users can upload insect images and receive predictions from both models, along with accuracy and descriptions.
 
 ## 🧠 Models
-- CNN model (`cnn_model.h5`)
-- MobileNet model (`mobilenet_model.h5`)
+- CNN model (`ProyekCV_model.h5`)
+- MobileNet model (`ProyekCV_model_v2.h5`)
 
 ## ⚙️ Tech Stack
-- FastAPI 
+- FastAPI
 - TensorFlow & Keras
 - HTML/CSS (for frontend)
 - Uvicorn (as ASGI server)
 - Python
-- NumPy & Pandas
-- Matplotlib & Seaborn
-- Scikit-learn
-
+- NumPy
+# - Pandas # Kamu tidak pakai Pandas di main.py, sebaiknya dihapus dari daftar
+# - Matplotlib & Seaborn # Kamu tidak pakai ini untuk runtime aplikasi, sebaiknya dihapus atau pindah ke "Development Dependencies"
+# - Scikit-learn # Kamu tidak pakai ini, sebaiknya dihapus
 
 ## 📦 Dataset
 
@@ -29,8 +38,6 @@ This project uses the [Insects Recognition Dataset](https://www.kaggle.com/datas
 
 The dataset was used to train both the CNN and MobileNet models included in this project.
 
-
-
 ## 🚀 How to Run Locally
 
 Make sure you have all dependencies installed and your virtual environment activated.
@@ -40,22 +47,5 @@ Open a terminal and run:
 
 ```bash
 venv\Scripts\activate
-uvicorn app.main:app --reload
-```
-
-The backend will be running at:
-http://127.0.0.1:8000
-
-**Step 2: Start a local HTTP server (for the frontend)**
-in another terminal, terminal, activate your virtual environment and run:
-
-```bash
-python -m http.server 8080
-```
-This will serve your frontend.html at:
-http://127.0.0.1:8080/frontend.html
-
-Now the frontend can communicate with the FastAPI backend.
-
-
-
+uvicorn main:app --reload --host 0.0.0.0 --port 8000 # <-- PERBAIKI INI: sesuaikan dengan command lokal mu
+```