Update app.py

app.py

@@ -1,67 +1,139 @@
 import gradio as gr
 from ultralytics import YOLO
 from PIL import Image
+import tensorflow as tf
+import numpy as np
 
-# Load YOLO model
-model = YOLO("Suspicious_Activities_nano.pt")
+# Global variables
+loaded_model = None
+selected_model = None
 
-# Define the prediction function
+# Load model on demand
+def load_model(choice):
+    global loaded_model, selected_model
+    selected_model = choice
+
+    if choice == "YOLO":
+        loaded_model = YOLO("Suspicious_Activities_nano.pt")
+        return "✅ YOLO model loaded successfully!"
+
+    elif choice == "SlowFast":
+        loaded_model = tf.keras.models.load_model("slowfast_finalmodel.h5")
+        return "✅ SlowFast model loaded successfully!"
+
+    else:
+        return "⚠️ Please select a valid model."
+
+
+# Prediction function
 def predict_suspicious_activity(image):
-    results = model.predict(source=image, show=False, conf=0.6)
-    results_img = results[0].plot()
-    return Image.fromarray(results_img)
+    global loaded_model, selected_model
+
+    if loaded_model is None:
+        return Image.new("RGB", (400, 200), (30, 30, 30))  # blank image
+
+    if selected_model == "YOLO":
+        results = loaded_model.predict(source=image, show=False, conf=0.6)
+        results_img = results[0].plot()
+        return Image.fromarray(results_img)
+
+    elif selected_model == "SlowFast":
+        img = image.resize((224, 224))
+        arr = np.expand_dims(np.array(img) / 255.0, axis=0)
+        preds = loaded_model.predict(arr)
+        class_id = np.argmax(preds)
+        return image  # placeholder – replace with visualization
 
-# Custom CSS for beauty ✨
+    return None
+
+
+# 🚀 Custom Attractive CSS
 custom_css = """
 #main-card {
-    background: rgba(255, 255, 255, 0.08);
-    backdrop-filter: blur(12px);
-    border-radius: 20px;
-    box-shadow: 0 8px 25px rgba(0,0,0,0.2);
-    padding: 30px;
+    background: linear-gradient(135deg, rgba(30,30,30,0.8), rgba(60,60,60,0.6));
+    backdrop-filter: blur(15px);
+    border-radius: 22px;
+    box-shadow: 0 10px 40px rgba(0,0,0,0.5);
+    padding: 35px;
+    border: 1px solid rgba(255,255,255,0.15);
+    transition: all 0.4s ease-in-out;
+}
+#main-card:hover {
+    transform: translateY(-4px);
+    box-shadow: 0 15px 45px rgba(0,0,0,0.65);
 }
 h1 {
-    font-size: 2.5rem !important;
-    background: linear-gradient(90deg, #ff4b1f, #1fddff);
+    font-size: 2.8rem !important;
+    font-weight: bold;
+    background: linear-gradient(90deg, #ff4b1f, #ff9068, #1fddff);
     -webkit-background-clip: text;
     -webkit-text-fill-color: transparent;
     text-align: center;
-    margin-bottom: 10px;
+    margin-bottom: 15px;
 }
 .description {
     text-align: center;
-    font-size: 1.1rem;
-    margin-bottom: 25px;
-    color: #ddd;
+    font-size: 1.15rem;
+    margin-bottom: 28px;
+    color: #f0f0f0;
 }
 .gr-button {
-    border-radius: 12px !important;
-    padding: 10px 20px !important;
-    font-weight: bold !important;
+    border-radius: 14px !important;
+    padding: 12px 24px !important;
+    font-weight: 600 !important;
+    letter-spacing: 0.5px;
+    background: linear-gradient(135deg, #ff4b1f, #1fddff) !important;
+    color: white !important;
+    border: none !important;
     transition: all 0.3s ease-in-out;
 }
 .gr-button:hover {
-    transform: scale(1.05);
-    box-shadow: 0 4px 15px rgba(0,0,0,0.3);
+    transform: scale(1.08) rotate(-1deg);
+    box-shadow: 0 6px 20px rgba(0,0,0,0.4);
+}
+.gr-button-secondary {
+    background: linear-gradient(135deg, #555, #333) !important;
+}
+label {
+    color: #ddd !important;
+    font-weight: 600;
 }
 """
 
-# Build modern UI
+# 🌟 Build modern UI
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
     with gr.Column(elem_id="main-card"):
         gr.Markdown("<h1>🚨 Suspicious Activity Detection</h1>")
-        gr.Markdown("<p class='description'>Upload an image and let YOLO detect suspicious activities instantly ⚡</p>")
+        gr.Markdown(
+            "<p class='description'>Choose a model (YOLO or SlowFast), upload your image, and let AI detect activities instantly ⚡</p>"
+        )
+
+        model_choice = gr.Dropdown(
+            choices=["YOLO", "SlowFast"], label="Select Model", value=None
+        )
+        load_status = gr.Label(label="Model Load Status")
+        load_btn = gr.Button("📥 Load Model")
 
         with gr.Row():
             input_image = gr.Image(type="pil", label="Upload Image", height=350)
             output_image = gr.Image(type="pil", label="Detection Result", height=350)
 
         with gr.Row():
-            detect_btn = gr.Button("🔍 Detect", variant="primary")
-            clear_btn = gr.Button("🗑️ Clear", variant="secondary")
+            detect_btn = gr.Button("🔍 Detect")
+            clear_btn = gr.Button("🗑️ Clear", elem_classes="gr-button-secondary")
 
+        load_btn.click(fn=load_model, inputs=model_choice, outputs=load_status)
         detect_btn.click(fn=predict_suspicious_activity, inputs=input_image, outputs=output_image)
         clear_btn.click(fn=lambda: (None, None), inputs=None, outputs=[input_image, output_image])
 
+        gr.Markdown(
+            """
+            ---
+            📂 **Dataset Reference:**  
+            [DCSASS Dataset on Kaggle](https://www.kaggle.com/mateohervas/dcsass-dataset)  
+            *(Used for training the SlowFast model)*
+            """
+        )
+
 # Launch
 demo.launch(share=True)