Update app.py

app.py

@@ -10,9 +10,9 @@ from huggingface_hub import hf_hub_download
 import warnings
 warnings.filterwarnings('ignore')
 
-# ============================================================
-# 1. LOAD MODELS (same as before)
-# ============================================================
+# ============================================
+# 1. LOAD MODELS
+# ============================================
 print("Loading YOLOv11 model from Hugging Face Hub...")
 model_path = hf_hub_download(
     repo_id="IsraInfo2004/drone-detection-yolov11",
@@ -30,9 +30,9 @@ blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image
 blip_model.eval()
 print("BLIP model loaded successfully.")
 
-# ============================================================
-# 2. HEATMAP FUNCTIONS (unchanged)
-# ============================================================
+# ============================================
+# 2. HEATMAP FUNCTIONS
+# ============================================
 layer_outputs = {}
 
 def hook_fn(module, input, output):
@@ -90,9 +90,9 @@ def generate_heatmap(model, image):
         print(f"Heatmap error: {e}")
         return None
 
-# ============================================================
+# ============================================
 # 3. DYNAMIC CAPTION (BLIP)
-# ============================================================
+# ============================================
 def generate_dynamic_caption(image):
     try:
         if isinstance(image, np.ndarray):
@@ -114,9 +114,9 @@ def generate_dynamic_caption(image):
         print(f"Caption error: {e}")
         return "AI model is analyzing the scene."
 
-# ============================================================
-# 4. XAI REPORT (English, professional)
-# ============================================================
+# ============================================
+# 4. XAI REPORT (ENGLISH)
+# ============================================
 def build_xai_report(is_drone, confidence, drone_count, processing_time, image_caption):
     confidence_percent = confidence * 100
     if is_drone:
@@ -209,9 +209,9 @@ Scattered activation pattern confirms absence of strong drone-like features.
 """
     return report
 
-# ============================================================
+# ============================================
 # 5. MAIN PIPELINE FUNCTION
-# ============================================================
+# ============================================
 def drone_detection_pipeline(input_image):
     try:
         if isinstance(input_image, Image.Image):
@@ -258,97 +258,49 @@ def drone_detection_pipeline(input_image):
         blank = np.zeros((480, 640, 3), dtype=np.uint8)
         return blank, blank, error_msg
 
-# ============================================================
-# 6. PROFESSIONAL GRADIO INTERFACE (NO EMOJIS, AI COLORS)
-# ============================================================
-custom_css = """
-body {
-    background-color: #0a0f1c;
-}
-.gradio-container {
-    background: linear-gradient(135deg, #0f172a 0%, #1e293b 100%);
-    font-family: 'Segoe UI', 'Roboto', sans-serif;
-}
-.gr-button-primary {
-    background: linear-gradient(90deg, #1e3a8a, #3b82f6) !important;
-    border: none !important;
-    color: white !important;
-    font-weight: 600 !important;
-    border-radius: 8px !important;
-    padding: 10px 24px !important;
-    transition: all 0.2s ease !important;
-}
-.gr-button-primary:hover {
-    transform: translateY(-2px);
-    box-shadow: 0 10px 20px -5px rgba(59,130,246,0.4);
-}
-.gr-tabs {
-    border: none;
-}
-.gr-tabs .tab-nav button {
-    background-color: #1e293b !important;
-    color: #cbd5e1 !important;
-    border-radius: 8px 8px 0 0 !important;
-    font-weight: 500 !important;
-}
-.gr-tabs .tab-nav button.selected {
-    background-color: #0f172a !important;
-    color: #3b82f6 !important;
-    border-bottom: 2px solid #3b82f6;
-}
-h1, h2, h3 {
-    color: #f0f9ff;
-}
-p, .gr-markdown, label {
-    color: #e2e8f0;
-}
-.gr-box, .gr-form {
-    background-color: #0f172a !important;
-    border: 1px solid #334155 !important;
-    border-radius: 12px !important;
-}
-"""
-
-with gr.Blocks(title="Drone Detection System", theme=gr.themes.Soft(), css=custom_css) as demo:
+# ============================================
+# 6. PROFESSIONAL INTERFACE (CLEAN, NO EMOJIS)
+# ============================================
+with gr.Blocks(title="Drone Detection System", theme=gr.themes.Soft()) as demo:
     gr.Markdown(
         """
         <div style="text-align: center; padding: 1rem 0 0.5rem 0;">
-            <h1 style="font-weight: 700; letter-spacing: -0.5px; margin-bottom: 0.2rem;">Drone Detection System</h1>
-            <p style="color: #94a3b8; font-size: 1rem;">YOLOv11 Object Detection | Explainable AI Heatmap | BLIP Captioning</p>
+            <h1 style="font-weight: 600; margin-bottom: 0.2rem;">Drone Detection System</h1>
+            <p style="font-size: 1rem; opacity: 0.8;">YOLOv11 | Explainable AI Heatmap | BLIP Captioning</p>
         </div>
         """
     )
     
-    with gr.Row(equal_height=False):
-        with gr.Column(scale=1, min_width=300):
-            input_image = gr.Image(label="Upload Image", type="pil", elem_classes="gr-box")
-            submit_btn = gr.Button("Analyze", variant="primary", size="lg")
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_image = gr.Image(label="Upload Image", type="pil")
+            analyze_btn = gr.Button("Analyze", variant="primary")
         with gr.Column(scale=2):
             with gr.Tabs():
-                with gr.TabItem("Detection Result"):
+                with gr.TabItem("Detection"):
                     output_image = gr.Image(label="Bounding Boxes")
-                with gr.TabItem("XAI Heatmap"):
-                    heatmap_image = gr.Image(label="Neural Activation Heatmap")
-                with gr.TabItem("XAI Report"):
-                    report_text = gr.Markdown(label="Interpretability Report")
+                with gr.TabItem("Heatmap"):
+                    heatmap_image = gr.Image(label="XAI Heatmap")
+                with gr.TabItem("Report"):
+                    report_text = gr.Markdown(label="XAI Analysis Report")
+    
+    analyze_btn.click(
+        fn=drone_detection_pipeline,
+        inputs=[input_image],
+        outputs=[output_image, heatmap_image, report_text]
+    )
     
     gr.Markdown(
         """
-        <div style="text-align: center; margin-top: 20px; font-size: 12px; color: #475569;">
-            <hr style="border-color: #334155;">
-            <p>Powered by YOLOv11, Gradio, Hugging Face Spaces | Model hosted on Hugging Face Hub</p>
+        <div style="text-align: center; margin-top: 20px; font-size: 12px; color: #666;">
+            <hr>
+            <p>Powered by YOLOv11, Gradio, Hugging Face Spaces</p>
         </div>
         """
     )
-    
-    submit_btn.click(
-        fn=drone_detection_pipeline,
-        inputs=[input_image],
-        outputs=[output_image, heatmap_image, report_text]
-    )
 
-# ============================================================
+# ============================================
 # 7. RUN APP
-# ============================================================
+# ============================================
 if __name__ == "__main__":
     demo.launch()