Upload streamlit_app.py

src/streamlit_app.py

@@ -1,13 +1,7 @@
 import streamlit as st
 import numpy as np
 from PIL import Image
-try:
-    import cv2
-except ImportError as e:
-    import subprocess
-    subprocess.run(["apt-get", "update"])
-    subprocess.run(["apt-get", "install", "-y", "libgl1"])
-    import cv2
+import cv2
 import tensorflow as tf
 from tensorflow.keras.preprocessing.image import img_to_array
 from tensorflow.keras.applications.vgg19 import preprocess_input
@@ -24,18 +18,8 @@ def pearson_corr(y_true, y_pred):
     y = y_pred - K.mean(y_pred)
     return K.sum(x * y) / (K.sqrt(K.sum(K.square(x))) * K.sqrt(K.sum(K.square(y))) + K.epsilon())
 
-# === Download model
-import gdown
-url = "https://drive.google.com/file/d/1XevL2OQH6i6vTRnK7GUc49x4OD6IEFxz/view?usp=sharing"  # NOT the share link
-output = "bmi_model_gender.keras"
-gdown.download(url, output, quiet=False)
-
 # === Load model and scaler ===
-# model = tf.keras.models.load_model("bmi_model_gender.keras", custom_objects={'pearson_corr': pearson_corr})
-model = tf.keras.models.load_model(
-    output,
-    custom_objects={'pearson_corr': pearson_corr}  # Include if used
-)
+model = tf.keras.models.load_model("bmi_model_gender.keras", custom_objects={'pearson_corr': pearson_corr})
 scaler = joblib.load("./label_scaler.pkl")
 
 # === Sidebar ===