Update app.py

app.py

@@ -1,75 +1,76 @@
-import streamlit as st
-import numpy as np
-from PIL import Image
-import os
-from ultralytics import YOLO
-
-# ── PAGE CONFIG ─────────────────────────────
-st.set_page_config(
-    page_title="SAR Ship Detection",
-    page_icon="🛰️",
-    layout="wide"
-)
-
-st.title("🛰️ SAR Ship Detection")
-
-# ── LOAD MODEL ─────────────────────────────
-@st.cache_resource
-def load_model():
-    try:
-        BASE_DIR = os.path.dirname(os.path.abspath(__file__))
-        MODEL_PATH = os.path.join(BASE_DIR, "model", "best.pt")
-
-        if not os.path.exists(MODEL_PATH):
-            st.error(f"Model not found at: {MODEL_PATH}")
-            return None
-
-        model = YOLO(MODEL_PATH)
-        return model
-
-    except Exception as e:
-        st.error(f"Error loading model: {e}")
-        return None
-
-
-model = load_model()
-
-# ── IMAGE UPLOAD ───────────────────────────
-uploaded_file = st.file_uploader(
-    "Upload SAR Image",
-    type=["png", "jpg", "jpeg", "tif", "tiff"]
-)
-
-# ── DETECTION ─────────────────────────────
-if uploaded_file is not None:
-
-    image = Image.open(uploaded_file).convert("RGB")
-    st.subheader("Original Image")
-    st.image(image, use_container_width=True)
-
-    if model is None:
-        st.error("Model not loaded.")
-    else:
-        img_np = np.array(image)
-
-        with st.spinner("Running detection..."):
-            results = model.predict(img_np, conf=0.35)
-
-        result = results[0]
-
-        # Annotated image
-        annotated = result.plot()
-        annotated = annotated[:, :, ::-1]
-
-        st.subheader("Detection Result")
-        st.image(annotated, use_container_width=True)
-
-        # Detection info
-        st.subheader("Detections")
-        if len(result.boxes) == 0:
-            st.write("No ships detected.")
-        else:
-            for i, box in enumerate(result.boxes):
-                conf = float(box.conf[0])
-                cls = int(box.cls[0])
-                st.write(f"Ship {i+1} → Confidence: {conf:.2f}")
+import streamlit as st
+import numpy as np
+from PIL import Image
+import os
+from ultralytics import YOLO
+
+# ── PAGE CONFIG ─────────────────────────────
+st.set_page_config(
+    page_title="SAR Ship Detection",
+    page_icon="🛰️",
+    layout="wide"
+)
+
+st.title("🛰️ SAR Ship Detection")
+
+# ── LOAD MODEL ─────────────────────────────
+@st.cache_resource
+def load_model():
+    try:
+        BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+        MODEL_PATH = os.path.join(BASE_DIR, "model", "best.pt")
+
+        if not os.path.exists(MODEL_PATH):
+            st.error(f"Model not found at: {MODEL_PATH}")
+            return None
+
+        model = YOLO(MODEL_PATH)
+        return model
+
+    except Exception as e:
+        st.error(f"Error loading model: {e}")
+        return None
+
+
+model = load_model()
+
+# ── IMAGE UPLOAD ───────────────────────────
+uploaded_file = st.file_uploader(
+    "Upload SAR Image",
+    type=["png", "jpg", "jpeg", "tif", "tiff"]
+)
+
+# ── DETECTION ─────────────────────────────
+if uploaded_file is not None:
+
+    image = Image.open(uploaded_file).convert("RGB")
+    st.subheader("Original Image")
+    st.image(image, use_container_width=True)
+
+    if model is None:
+        st.error("Model not loaded.")
+    else:
+        img_np = np.array(image)
+
+        with st.spinner("Running detection..."):
+            results = model.predict(img_np, conf=0.35)
+
+        result = results[0]
+
+        # Annotated image
+        annotated = result.plot()
+        annotated = annotated[:, :, ::-1]
+
+        st.subheader("Detection Result")
+        st.image(annotated, use_container_width=True)
+
+        # Detection info
+        st.subheader("Detections")
+        if len(result.boxes) == 0:
+            st.write("No ships detected.")
+        else:
+            for i, box in enumerate(result.boxes):
+                conf = float(box.conf[0])
+                cls = int(box.cls[0])
+                st.write(f"Ship {i+1} → Confidence: {conf:.2f}")
+                st.write("Model status:", "Loaded ✅" if model else "Not Loaded ❌")