Update app.py

app.py

@@ -99,30 +99,34 @@ def get_first_aid_recommendation(wound_class):
 
 # --- SCRIPT JAVASCRIPT UNTUK GPS ---
 get_location_js = """
-function getGeoLocation() {
-    return new Promise((resolve, reject) => {
-        navigator.geolocation.getCurrentPosition(
-            (position) => {
-                resolve(`${position.coords.latitude},${position.coords.longitude}`);
-            },
-            (error) => {
-                resolve("Lokasi tidak diizinkan");
-            }
-        );
-    });
+async () => {
+    if (!navigator.geolocation) {
+        return "Browser tidak mendukung GPS";
+    }
+    try {
+        const pos = await new Promise((res, rej) => {
+            navigator.geolocation.getCurrentPosition(res, rej, {timeout: 5000});
+        });
+        return `${pos.coords.latitude}, ${pos.coords.longitude}`;
+    } catch (err) {
+        return "Lokasi tidak dapat diakses (Izin ditolak/Timeout)";
+    }
 }
 """
 
 def predict_image(image_input, location_data):
     if best_model is None:
-        return {}, "⚠️ Model tidak ditemukan.", ""
+        return {}, "⚠️ Model tidak ditemukan.", "Lokasi tidak dicek"
     if image_input is None:
         return {}, "Silakan upload gambar.", ""
 
-    # Info Lokasi
-    info_lokasi = f"📍 **Koordinat Pengunggahan:** {location_data}" if location_data else "📍 Lokasi tidak terdeteksi."
+    # Logika pesan lokasi: Tetap munculkan hasil meskipun lokasi gagal
+    if not location_data or "tidak" in location_data.lower():
+        status_lokasi = f"⚠️ **{location_data if location_data else 'Lokasi tidak terdeteksi'}**"
+    else:
+        status_lokasi = f"📍 **Lokasi:** {location_data}"
 
-    # Preprocessing & Prediksi
+    # --- Preprocessing & Prediksi ---
     img = image_input.resize(IMG_SIZE)
     img_array = tf.keras.utils.img_to_array(img) / 255.0
     img_array = tf.expand_dims(img_array, 0)
@@ -142,7 +146,7 @@ def predict_image(image_input, location_data):
     THRESHOLD = 0.20
     if top_confidence < THRESHOLD:
         top_label_id = "Normal (Tidak Terdeteksi)"
-        rekomendasi_teks = "Model kurang akurat. Pastikan foto jelas."
+        rekomendasi_teks = "Model kurang akurat. Pastikan foto jelas dan terang."
     else:
         top_label_id = translation_map.get(top_label_en, top_label_en)
         rekomendasi_teks = get_first_aid_recommendation(top_label_en)
@@ -153,31 +157,29 @@ def predict_image(image_input, location_data):
         f"--- \n*Tingkat Keyakinan AI: {top_confidence:.2%}*"
     )
     
-    return translated_output_dict, formatted_output, info_lokasi
+    return translated_output_dict, formatted_output, status_lokasi
 
 # --- UI INTERFACE ---
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="red", secondary_hue="slate")) as demo:
     gr.Markdown("# 🚨 FirstAidLens")
     
-    # Input tersembunyi untuk menampung data dari JS
     location_hidden = gr.Textbox(visible=False)
     
     with gr.Row():
         with gr.Column(scale=1):
-            input_img = gr.Image(sources=["upload", "webcam"], type="pil", label="Ambil Foto Luka")
+            input_img = gr.Image(sources=["upload", "webcam"], type="pil", label="Foto Luka")
             btn_predict = gr.Button("Analisis Luka & Ambil Lokasi", variant="primary")
             
         with gr.Column(scale=1):
             output_label = gr.Label(num_top_classes=3, label="Hasil Analisis")
             output_markdown = gr.Markdown("### Panduan Pertolongan Pertama")
-            output_location = gr.Markdown("") # Menampilkan lokasi di sini
+            output_location = gr.Markdown("") 
 
-    # Alur Klik: Jalankan JS dulu untuk isi location_hidden, lalu jalankan predict_image
     btn_predict.click(
         fn=predict_image,
         inputs=[input_img, location_hidden],
         outputs=[output_label, output_markdown, output_location],
-        js=get_location_js
+        js=get_location_js # JS akan mengisi location_hidden sebelum fn dipanggil
     )
 
 if __name__ == "__main__":