Upload app.py

app.py

@@ -80,13 +80,15 @@ import numpy as np
 import tensorflow as tf
 from tensorflow.keras.models import load_model
 from PIL import Image
-import cv2
 import os
 
-# Load the model
-model = tf.keras.models.load_model("model_n.keras")
+# Check if running on Hugging Face Spaces
+on_huggingface = os.environ.get("SPACE_ID") is not None
 
+# Load model
+model = tf.keras.models.load_model("model_n.keras")
 
+# Class names
 class_names = [
     'Bush Clock Vine', 'Common Lanthana', 'Datura', 'Hibiscus', 'Jatropha', 'Marigold',
     'Nityakalyani', 'Rose', 'Yellow_Daisy', 'adathoda', 'banana', 'champaka', 'chitrak',
@@ -95,23 +97,21 @@ class_names = [
     'thumba', 'touch me not', 'tridax procumbens', 'wild_potato_vine'
 ]
 
+# Title
+st.title("🌼 Flower Identifier")
 
-on_huggingface = os.environ.get("SPACE_ID") is not None
-
-
-st.title(" Flower Identifier")
-
-
+# Choose mode
 if on_huggingface:
-    st.warning("Real-time camera is not supported on Hugging Face Spaces. Please upload an image.")
+    st.warning("Real-time camera is not supported on Hugging Face. Please upload an image.")
     mode = "Upload Image"
 else:
     mode = st.radio("Choose input method:", ["Upload Image", "Real-Time Camera"])
 
+# Upload image mode
 if mode == "Upload Image":
     st.markdown("### Upload an image of a flower")
     img = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
-    
+
     if img is not None:
         st.image(img, caption="Uploaded Image", use_column_width=True)
 
@@ -126,10 +126,12 @@ if mode == "Upload Image":
             confidence = round(100 * np.max(prediction[0]), 2)
             flower_name = class_names[predicted_class]
 
-            st.success(f" Predicted Flower: **{flower_name}**")
+            st.success(f"🌸 Predicted Flower: **{flower_name}**")
             st.info(f"🔍 Confidence: **{confidence}%**")
 
+# Real-time camera mode (local only)
 elif mode == "Real-Time Camera":
+    import cv2  # <- import only if needed
     st.markdown("### Real-Time Flower Recognition")
     run = st.checkbox('Start Camera')
     FRAME_WINDOW = st.image([])
@@ -141,7 +143,7 @@ elif mode == "Real-Time Camera":
         while run:
             ret, frame = cap.read()
             if not ret:
-                st.warning("Failed to access camera.")
+                st.warning("⚠️ Failed to access camera.")
                 break
 
             img_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
@@ -153,7 +155,7 @@ elif mode == "Real-Time Camera":
             confidence = round(100 * np.max(predictions[0]), 2)
             flower_name = class_names[predicted_class]
 
-            cv2.putText(frame, f"{flower_name} ({confidence}%)", (10, 30), 
+            cv2.putText(frame, f"{flower_name} ({confidence}%)", (10, 30),
                         cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2, cv2.LINE_AA)
 
             FRAME_WINDOW.image(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))