Update app.py

app.py

@@ -10,22 +10,29 @@ from ultralytics import YOLO
 from openai import OpenAI
 
 from docx import Document
-from docx.shared import Inches
 
 
 # =====================================================
-# MODEL
+# MODEL PATHS
 # =====================================================
 
-MODEL_PATH = "best_asphalt.pt"
-model = YOLO(MODEL_PATH)
+MODEL_PATHS = {
+    "Asphalt Pathologies Detection": "best_asphalt.pt",
+    "Concrete Pathologies Detection": "Concreate_defect_detection.pt",
+    "Facades Pathologies Detection": "Facades_defect_detection.pt"
+}
+
+models = {
+    name: YOLO(path)
+    for name, path in MODEL_PATHS.items()
+}
 
 
 # =====================================================
 # GROK / XAI API
 # =====================================================
 
-XAI_API_KEY = os.getenv("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")
+XAI_API_KEY = os.getenv("XAI_API_KEY")
 
 client = OpenAI(
     api_key=XAI_API_KEY,
@@ -47,10 +54,25 @@ def normalize_class_name(name):
 
 
 # =====================================================
-# PATHOLOGY CATALOG
+# REPORT TITLE
+# =====================================================
+
+def get_report_title(selected_model):
+    if "Asphalt" in selected_model:
+        return "Civil Engineering Asphalt Pavement Inspection Report"
+    elif "Concrete" in selected_model:
+        return "Civil Engineering Concrete Pathology Inspection Report"
+    elif "Facades" in selected_model:
+        return "Civil Engineering Facade Pathology Inspection Report"
+    else:
+        return "Civil Engineering Pathology Inspection Report"
+
+
+# =====================================================
+# ASPHALT PATHOLOGY CATALOG
 # =====================================================
 
-PATHOLOGY_CATALOG = {
+ASPHALT_CATALOG = {
     "01LONGITUDINAL CRACKS": {
         "name": "Longitudinal Cracks",
         "severity": "Medium",
@@ -75,20 +97,12 @@ PATHOLOGY_CATALOG = {
         "risk": "Advanced structural fatigue, pothole formation, and possible pavement collapse.",
         "recommendation": "Mill affected layers and reconstruct pavement structure. Perform geotechnical investigation if widespread."
     },
-    "04REFLECTION CRACKS": {
-        "name": "Reflection Cracks",
-        "severity": "Medium–High",
-        "priority": "P2",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Water ingress, internal erosion, and pothole formation.",
-        "recommendation": "Seal with elastomeric mastic. For resurfacing, use anti-crack geogrid or SAMI membrane."
-    },
     "05POTHOLES": {
         "name": "Potholes",
         "severity": "High",
         "priority": "P1",
         "deadline": "Immediate: within 24–48 hours",
-        "risk": "Direct accident risk, especially for motorcycles and bicycles; vehicle tire and suspension damage.",
+        "risk": "Direct accident risk, especially for motorcycles and bicycles.",
         "recommendation": "Immediate patching with hot/cold bituminous mix. Cut edges, clean, prime, fill, and compact."
     },
     "06RUTTING": {
@@ -97,31 +111,7 @@ PATHOLOGY_CATALOG = {
         "priority": "P1/P2",
         "deadline": "Short term if rut depth exceeds 15–20 mm",
         "risk": "Aquaplaning, vehicle instability, and progressive lower-layer degradation.",
-        "recommendation": "Mill affected area and replace with high-stability asphalt mix such as SMA or BBTM."
-    },
-    "07UNDULATIONS AND CORRUGATION": {
-        "name": "Undulations and Corrugation",
-        "severity": "Medium",
-        "priority": "P2/P3",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Loss of driving comfort, braking instability, and possible vehicle control issues.",
-        "recommendation": "Mill wearing course and replace with deformation-resistant asphalt mixture."
-    },
-    "08DEPRESSIONS AND SETTLEMENTS": {
-        "name": "Depressions and Settlements",
-        "severity": "High",
-        "priority": "P1",
-        "deadline": "Immediate if depression exceeds 3 cm",
-        "risk": "Water accumulation, aquaplaning, and potential sudden pavement collapse.",
-        "recommendation": "Investigate cause using GPR/load tests. Repair underlying cause before structural reconstruction."
-    },
-    "09SWELLING": {
-        "name": "Swelling / Bulges",
-        "severity": "Medium–High",
-        "priority": "P1/P2",
-        "deadline": "Short term; immediate if height exceeds 5 cm",
-        "risk": "Vehicle instability and fall risk for cyclists/pedestrians.",
-        "recommendation": "Investigate cause such as roots, frost, leakage, or expansive soil. Remove cause, mill, and level area."
+        "recommendation": "Mill affected area and replace with high-stability asphalt mix."
     },
     "10SURFACE RAVELING": {
         "name": "Surface Raveling",
@@ -130,152 +120,28 @@ PATHOLOGY_CATALOG = {
         "deadline": "Medium term: 1–3 months",
         "risk": "Loose aggregate, reduced traction, water penetration, and future pothole formation.",
         "recommendation": "Apply slurry seal, microsurfacing, or mill and resurface if advanced."
-    },
-    "11PEELING AND LAYER DETACHMENT": {
-        "name": "Peeling and Layer Detachment",
-        "severity": "High",
-        "priority": "P1",
-        "deadline": "Immediate; remove loose material within 24 hours",
-        "risk": "Loose material causing motorcyclist/cyclist falls and rapid base exposure.",
-        "recommendation": "Remove loose material, mill affected area, clean, apply proper tack coat, and resurface."
-    },
-    "12BINDER BLEEDING": {
-        "name": "Binder Bleeding / Exudation",
-        "severity": "Medium; High on curves/intersections",
-        "priority": "P1/P3",
-        "deadline": "Short term; immediate on sharp curves",
-        "risk": "Loss of skid resistance and accident risk in wet/hot conditions.",
-        "recommendation": "Apply cover aggregate and compact lightly. In severe cases, micro-mill and replace surface layer."
-    },
-    "13AGGREGATE POLISHING": {
-        "name": "Aggregate Polishing",
-        "severity": "Medium; High in wet/slope areas",
-        "priority": "P1",
-        "deadline": "Short term: less than 1 month",
-        "risk": "Loss of wet skid resistance and increased braking distance.",
-        "recommendation": "Apply anti-skid surface treatment or overlay with high-CPA aggregate mix."
-    },
-    "14PAVEMENT SHOULDER LEVEL DIFFERENCE": {
-        "name": "Pavement–Shoulder Level Difference",
-        "severity": "High",
-        "priority": "P1",
-        "deadline": "Short term; immediate if level difference exceeds 8 cm",
-        "risk": "Vehicle rollover risk and abrupt re-entry collision risk.",
-        "recommendation": "Level shoulder to roadway or construct transition ramp with maximum slope 1:6."
-    },
-    "15CONSTRUCTION JOINT DETERIORATION": {
-        "name": "Construction Joint Deterioration",
-        "severity": "Medium",
-        "priority": "P2/P3",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Water infiltration and progressive deterioration along joint line.",
-        "recommendation": "Seal joint with elastomeric bituminous mastic. Mill and rebuild severely deteriorated joints."
-    },
-    "16CRESCENT CRACKS": {
-        "name": "Crescent-Shaped / Slippage Cracks",
-        "severity": "High",
-        "priority": "P1",
-        "deadline": "Short term or immediate if active detachment exists",
-        "risk": "Layer sliding, material detachment, and direct danger to motorcycles.",
-        "recommendation": "Mill affected area and replace with proper tack coat and compacted asphalt layer."
-    },
-    "17CHANNELS AND DEEP GROOVES": {
-        "name": "Channels and Deep Grooves",
-        "severity": "Medium; High if depth exceeds 2 cm",
-        "priority": "P2",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Aquaplaning and fall risk for motorcycles/cyclists.",
-        "recommendation": "Mill and resurface with abrasion-resistant mix. Correct surface drainage."
-    },
-    "18LATERAL DISPLACEMENT": {
-        "name": "Lateral Displacement / Shoving",
-        "severity": "Medium; High in turning areas",
-        "priority": "P2/P3",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Vehicle instability on curves and cyclist risk near displaced material.",
-        "recommendation": "Mill affected area and replace with high-stability polymer-modified mix."
-    },
-    "20WATER SEEPAGE": {
-        "name": "Water Seepage / Wet Areas",
-        "severity": "High",
-        "priority": "P1/P2",
-        "deadline": "Immediate investigation within 24–48 hours",
-        "risk": "Internal erosion, loss of bearing capacity, and possible pavement collapse.",
-        "recommendation": "Investigate drainage/leakage source, repair water source, drain retained water, and reconstruct affected pavement."
-    },
-    "21PERIMETER DETERIORATION OF MANHOLES": {
-        "name": "Perimeter Deterioration of Manholes",
-        "severity": "High",
-        "priority": "P1",
-        "deadline": "Short term; immediate if level difference exceeds 2 cm or loose material exists",
-        "risk": "Cyclist/motorcyclist falls, vehicle impact damage, and water ingress.",
-        "recommendation": "Demolish perimeter, adjust frame level, and replace pavement with compacted hot mix."
-    },
-    "22EDGE DETERIORATION": {
-        "name": "Road Edge Deterioration",
-        "severity": "Medium; High if shoulder level difference exists",
-        "priority": "P1/P3",
-        "deadline": "Medium term; immediate if associated with dangerous level difference",
-        "risk": "Loss of vehicle control when moving to shoulder and progressive edge failure.",
-        "recommendation": "Cut deteriorated edge, replace with compacted hot mix, and restore shoulder continuity."
-    },
-    "23PATCHES IN POOR CONDITION": {
-        "name": "Patches in Poor Condition",
-        "severity": "Medium; High if level difference exceeds 2 cm",
-        "priority": "P1/P2",
-        "deadline": "Short term; immediate if level difference exceeds 2 cm",
-        "risk": "Uneven surface, fall risk, aggregate projection, and unresolved underlying defect.",
-        "recommendation": "Mill and repatch correctly using straight cut, priming, hot mix, and layer compaction."
-    },
-    "24MARKING DAMAGE": {
-        "name": "Horizontal Marking Damage",
-        "severity": "Medium; High at pedestrian crossings/intersections",
-        "priority": "P1/P3",
-        "deadline": "Short term at intersections; long term for secondary markings",
-        "risk": "Driver disorientation, lane invasion, and pedestrian crossing visibility loss.",
-        "recommendation": "Clean surface and repaint/apply thermoplastic marking with glass microspheres."
-    },
-    "25STEP BETWEEN LANES": {
-        "name": "Step Between Lanes",
-        "severity": "Medium; High if step exceeds 3 cm",
-        "priority": "P1/P2",
-        "deadline": "Short term: less than 1 month",
-        "risk": "Motorcycle instability during lane changes and water retention.",
-        "recommendation": "Mill transition zone and level the step using a ramp with maximum slope 1:10."
-    },
-    "26THERMAL FATIGUE CRACKING": {
-        "name": "Thermal Fatigue Cracking",
-        "severity": "Medium",
-        "priority": "P2",
-        "deadline": "Medium term: 1–3 months",
-        "risk": "Water infiltration, freeze-thaw damage, and evolution to structural cracking.",
-        "recommendation": "Seal cracks and use polymer-modified bitumen with suitable low-temperature performance in resurfacing."
-    },
-    "27CHEMICAL AGENTS": {
-        "name": "Deterioration due to Hydrocarbons / Chemical Agents",
-        "severity": "Medium–High",
-        "priority": "P1/P2",
-        "deadline": "Short term: less than 1 month",
-        "risk": "Softened asphalt, soil/groundwater contamination, and slippery surface.",
-        "recommendation": "Apply absorbents, mill contaminated area, manage waste properly, and replace with resistant asphalt mix."
-    },
-    "28OXIDATION AND AGING OF BINDER": {
-        "name": "Oxidation and Aging of Binder",
-        "severity": "Medium",
-        "priority": "P3",
-        "deadline": "Long term: 3–6 months",
-        "risk": "Reduced pavement life, brittleness, cracking, and surface disintegration.",
-        "recommendation": "Apply rejuvenating treatment or slurry seal. Plan resurfacing before structural cracking occurs."
     }
 }
 
 
+# =====================================================
+# SELECT CATALOG
+# =====================================================
+
+def get_catalog(selected_model):
+    if "Asphalt" in selected_model:
+        return ASPHALT_CATALOG
+    else:
+        return {}
+
+
 # =====================================================
 # DETECTION HELPERS
 # =====================================================
 
-def get_detection_summary(results):
+def get_detection_summary(results, selected_model):
     detections = []
+    model = models[selected_model]
 
     for r in results:
         if r.boxes is None:
@@ -290,6 +156,7 @@ def get_detection_summary(results):
             key = normalize_class_name(raw_name)
 
             detections.append({
+                "model": selected_model,
                 "class": raw_name,
                 "key": key,
                 "confidence": round(conf, 3),
@@ -326,38 +193,41 @@ def summarize_detections(detections):
 # BASIC ENGINEERING REPORT
 # =====================================================
 
-def basic_engineering_report(detections):
+def basic_engineering_report(detections, selected_model):
     summary = summarize_detections(detections)
+    catalog = get_catalog(selected_model)
+    title = get_report_title(selected_model)
 
     if summary["total"] == 0:
-        return """
-# Civil Engineering Pavement Inspection Report
+        return f"""
+# {title}
 
 ## Detection Result
-No pavement pathology was detected with the selected confidence threshold.
+No pathology was detected with the selected confidence threshold.
 
 ## Engineering Interpretation
-The inspected image/video does not show a clear asphalt defect detectable by the model. This does not guarantee that the pavement is defect-free.
+The inspected image/video does not show a clear defect detectable by the selected model. This does not guarantee that the element is defect-free.
 
 ## Recommended Action
 - Repeat inspection with clearer images.
-- Capture the road surface perpendicular to the pavement.
+- Capture the surface perpendicular to the inspected element.
 - Use manual visual inspection for confirmation.
-- Reduce the confidence threshold if the image contains small or low-contrast defects.
+- Reduce the confidence threshold if small or low-contrast defects are expected.
 
 ## Disclaimer
-This report is AI-assisted and must be verified by a qualified civil/pavement engineer.
+This report is AI-assisted and must be verified by a qualified civil engineer.
 """
 
     lines = []
 
-    lines.append("# Civil Engineering Pavement Inspection Report")
+    lines.append(f"# {title}")
     lines.append("")
     lines.append("## 1. AI Detection Summary")
+    lines.append(f"- Selected model: {selected_model}")
     lines.append(f"- Total detected defects: {summary['total']}")
 
     for cls, count in summary["classes"].items():
-        info = PATHOLOGY_CATALOG.get(cls)
+        info = catalog.get(cls)
         label = info["name"] if info else cls.title()
         lines.append(f"- {label}: {count} detected area(s)")
 
@@ -365,7 +235,7 @@ This report is AI-assisted and must be verified by a qualified civil/pavement en
     lines.append("## 2. Engineering Diagnosis")
 
     for cls, count in summary["classes"].items():
-        info = PATHOLOGY_CATALOG.get(cls)
+        info = catalog.get(cls)
 
         if info:
             lines.append("")
@@ -385,23 +255,22 @@ This report is AI-assisted and must be verified by a qualified civil/pavement en
 
     lines.append("")
     lines.append("## 3. Field Verification Checklist")
-    lines.append("- Measure crack width, pothole depth, rut depth, or level difference where applicable.")
-    lines.append("- Record GPS location and chainage/station of each defect.")
+    lines.append("- Measure crack width, spalling depth, pothole depth, deformation, delamination, or level difference where applicable.")
+    lines.append("- Record GPS location and inspection area.")
     lines.append("- Capture georeferenced photographs before repair.")
-    lines.append("- Check drainage condition and evidence of water infiltration.")
-    lines.append("- Confirm whether loose material creates immediate user risk.")
-    lines.append("- Consider traffic volume, heavy vehicle loading, and vulnerable road users.")
+    lines.append("- Check drainage, moisture ingress, and evidence of progressive deterioration.")
+    lines.append("- Confirm whether loose material creates immediate public safety risk.")
 
     lines.append("")
     lines.append("## 4. Professional Notes")
-    lines.append("- P1 defects require urgent safety management, including warning signs or cordoning if immediate repair is not possible.")
+    lines.append("- P1 defects require urgent safety management.")
     lines.append("- P2 defects should be included in the structural maintenance plan.")
     lines.append("- P3 defects can generally be included in routine preventive maintenance.")
-    lines.append("- Final maintenance decisions should be confirmed by an on-site civil/pavement engineer.")
+    lines.append("- Final maintenance decisions should be confirmed by an on-site civil engineer.")
 
     lines.append("")
     lines.append("## 5. Disclaimer")
-    lines.append("This report is generated using AI-based image/video detection and a technical pavement pathology catalog. It is intended for preliminary engineering support only and must not replace field inspection, laboratory testing, or professional engineering judgment.")
+    lines.append("This report is generated using AI-based image/video detection. It is intended for preliminary engineering support only and must not replace field inspection, testing, or professional engineering judgment.")
 
     return "\n".join(lines)
 
@@ -410,21 +279,23 @@ This report is AI-assisted and must be verified by a qualified civil/pavement en
 # GROK ENGINEERING REPORT
 # =====================================================
 
-def grok_engineering_report(detections):
-    base_report = basic_engineering_report(detections)
+def grok_engineering_report(detections, selected_model):
+    base_report = basic_engineering_report(detections, selected_model)
 
     if client is None:
         return base_report + "\n\n⚠️ Grok API key not found. Add `XAI_API_KEY` in Hugging Face Space Secrets."
 
     prompt = f"""
-You are a professional civil pavement engineer.
+You are a professional civil engineering inspection expert.
 
-Generate a formal engineering inspection report based on the following YOLO asphalt pavement detections.
+Generate a formal engineering inspection report for:
+
+{selected_model}
 
 Use this structure:
 1. Project title
 2. AI detection summary
-3. Identified asphalt pathologies
+3. Identified pathologies
 4. Probable causes
 5. Severity and priority
 6. Associated civil engineering risks
@@ -433,19 +304,10 @@ Use this structure:
 9. Field verification checklist
 10. Disclaimer
 
-Use this logic:
-- P1 = direct third-party/user safety risk.
-- P2 = structural degradation risk.
-- P3 = superficial degradation.
-- High severity defects require immediate or short-term action.
-- Potholes, settlements, peeling, dangerous unevenness, water seepage, and loose material are urgent.
-- Cracking and rutting may indicate structural degradation.
-- Water infiltration accelerates pavement deterioration.
-
-Detected data:
+Detected YOLO data:
 {json.dumps(detections, indent=2)}
 
-Local catalog interpretation:
+Local report:
 {base_report}
 """
 
@@ -453,8 +315,14 @@ Local catalog interpretation:
         response = client.chat.completions.create(
             model="grok-3-mini",
             messages=[
-                {"role": "system", "content": "You are a civil engineering pavement inspection expert."},
-                {"role": "user", "content": prompt}
+                {
+                    "role": "system",
+                    "content": "You are a civil engineering pathology inspection expert."
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
             ],
             temperature=0.2
         )
@@ -469,10 +337,10 @@ Local catalog interpretation:
 # WORD REPORT
 # =====================================================
 
-def create_word_report(report_text):
+def create_word_report(report_text, selected_model):
     doc = Document()
 
-    doc.add_heading("Civil Engineering Pavement Inspection Report", level=1)
+    doc.add_heading(get_report_title(selected_model), level=1)
 
     for line in report_text.split("\n"):
         line = line.strip()
@@ -509,10 +377,12 @@ def create_word_report(report_text):
 # IMAGE DETECTION
 # =====================================================
 
-def detect_image(image, conf):
+def detect_image(image, conf, selected_model):
     if image is None:
         return None, "Please upload an image.", "", None
 
+    model = models[selected_model]
+
     results = model.predict(
         source=image,
         imgsz=640,
@@ -524,9 +394,9 @@ def detect_image(image, conf):
     plotted = cv2.cvtColor(plotted, cv2.COLOR_BGR2RGB)
     output_img = Image.fromarray(plotted)
 
-    detections = get_detection_summary(results)
-    report = grok_engineering_report(detections)
-    word_file = create_word_report(report)
+    detections = get_detection_summary(results, selected_model)
+    report = grok_engineering_report(detections, selected_model)
+    word_file = create_word_report(report, selected_model)
 
     return output_img, json.dumps(detections, indent=2), report, word_file
 
@@ -535,10 +405,12 @@ def detect_image(image, conf):
 # VIDEO DETECTION
 # =====================================================
 
-def detect_video(video_path, conf):
+def detect_video(video_path, conf, selected_model):
     if video_path is None:
         return None, "Please upload a video.", "", None
 
+    model = models[selected_model]
+
     cap = cv2.VideoCapture(video_path)
 
     if not cap.isOpened():
@@ -560,8 +432,6 @@ def detect_video(video_path, conf):
 
     all_detections = []
     frame_count = 0
-
-    # Process every 3rd frame to reduce runtime
     process_every_n_frames = 3
     last_annotated = None
 
@@ -580,7 +450,7 @@ def detect_video(video_path, conf):
                 verbose=False
             )
 
-            detections = get_detection_summary(results)
+            detections = get_detection_summary(results, selected_model)
             all_detections.extend(detections)
 
             annotated = results[0].plot()
@@ -595,8 +465,8 @@ def detect_video(video_path, conf):
     cap.release()
     writer.release()
 
-    report = grok_engineering_report(all_detections)
-    word_file = create_word_report(report)
+    report = grok_engineering_report(all_detections, selected_model)
+    word_file = create_word_report(report, selected_model)
 
     return output_path, json.dumps(all_detections[:100], indent=2), report, word_file
 
@@ -605,17 +475,26 @@ def detect_video(video_path, conf):
 # GRADIO UI
 # =====================================================
 
-with gr.Blocks(title="Asphalt Pavement Defect Detection + Engineering Report") as demo:
+with gr.Blocks(title="Civil Infrastructure Pathology Detection + Engineering Report") as demo:
 
     gr.Markdown("""
-# Asphalt Pavement Defect Detection and Civil Engineering Report
+# Civil Infrastructure Pathology Detection and Engineering Report
 
-Upload an asphalt pavement **image or video**.  
-The YOLOv8 model detects pavement defects and generates a civil engineering report based on the pavement pathology catalog.
+Upload an image or video and select one of the three trained YOLO models:
 
-The report can also be downloaded as a **Word document (.docx)**.
+- Asphalt pathologies detection
+- Concrete pathologies detection
+- Facades pathologies detection
+
+The app generates detection results and a downloadable Word engineering report.
 """)
 
+    selected_model = gr.Dropdown(
+        choices=list(MODEL_PATHS.keys()),
+        value="Asphalt Pathologies Detection",
+        label="Select Detection Model"
+    )
+
     conf = gr.Slider(
         minimum=0.10,
         maximum=0.90,
@@ -625,7 +504,7 @@ The report can also be downloaded as a **Word document (.docx)**.
     )
 
     with gr.Tab("Image Detection"):
-        image_input = gr.Image(type="pil", label="Upload Asphalt Image")
+        image_input = gr.Image(type="pil", label="Upload Image")
         image_output = gr.Image(type="pil", label="Detection Output")
         image_json = gr.Textbox(label="Raw Detection Data", lines=8)
         image_report = gr.Markdown(label="Engineering Report")
@@ -635,12 +514,12 @@ The report can also be downloaded as a **Word document (.docx)**.
 
         image_btn.click(
             fn=detect_image,
-            inputs=[image_input, conf],
+            inputs=[image_input, conf, selected_model],
             outputs=[image_output, image_json, image_report, image_docx]
         )
 
     with gr.Tab("Video Detection"):
-        video_input = gr.Video(label="Upload Asphalt Video")
+        video_input = gr.Video(label="Upload Video")
         video_output = gr.Video(label="Detection Output Video")
         video_json = gr.Textbox(label="Raw Detection Data - First 100 Detections", lines=8)
         video_report = gr.Markdown(label="Engineering Report")
@@ -650,22 +529,23 @@ The report can also be downloaded as a **Word document (.docx)**.
 
         video_btn.click(
             fn=detect_video,
-            inputs=[video_input, conf],
+            inputs=[video_input, conf, selected_model],
             outputs=[video_output, video_json, video_report, video_docx]
         )
 
     gr.Markdown("""
 ## Notes
-- Use clear road-surface images for better detection.
+- Upload the correct type of image/video for the selected model.
 - For video, every 3rd frame is processed to reduce runtime.
-- Add `XAI_API_KEY` in Hugging Face Space Secrets to enable Grok-generated professional reporting.
+- Add `XAI_API_KEY` in Hugging Face Space Secrets to enable Grok-generated reporting.
 - If no API key is added, the app still generates a local engineering report.
 - The report is AI-assisted and must be verified by a qualified civil engineer.
 """)
 
+
 if __name__ == "__main__":
     demo.launch(
-    server_name="0.0.0.0",
-    server_port=7860,
-    ssr_mode=False
-)
+        server_name="0.0.0.0",
+        server_port=7860,
+        ssr_mode=False
+    )