Add Gradio demo app for PPE detection

gradio_app.py

@@ -0,0 +1,110 @@
+"""
+Gradio App for PPE Compliance Detection
+Run: gradio gradio_app.py
+"""
+import gradio as gr
+from ultralytics import YOLO
+from huggingface_hub import hf_hub_download
+from PIL import Image
+import cv2
+import numpy as np
+
+MODEL_ID = "baskarmother/yolov8-ppe-construction"
+CLASS_NAMES = [
+    'barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask',
+    'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net',
+    'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader'
+]
+
+def get_color(label):
+    if label in ["hardhat", "mask", "safety vest", "gloves", "safety shoes"]:
+        return (0, 255, 0)  # Green = compliant PPE
+    elif label in ["no-hardhat", "no-mask", "no-safety vest"]:
+        return (0, 0, 255)  # Red = violation
+    else:
+        return (255, 0, 0)  # Blue = other
+
+# Load model once
+print("Loading model from Hub...")
+weights_path = hf_hub_download(MODEL_ID, "best.pt")
+model = YOLO(weights_path)
+print("Model loaded!")
+
+def detect_ppe(image, conf_threshold=0.25):
+    results = model(image, conf=conf_threshold)
+    result = results[0]
+    
+    # Convert PIL to numpy array
+    img = np.array(image)
+    img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+    
+    detections = []
+    compliance = {"hardhat": "NOT DETECTED", "mask": "NOT DETECTED", "safety_vest": "NOT DETECTED"}
+    detected_classes = set()
+    
+    for box in result.boxes:
+        x1, y1, x2, y2 = map(int, box.xyxy[0])
+        cls_id = int(box.cls[0])
+        conf = float(box.conf[0])
+        label = CLASS_NAMES[cls_id]
+        detected_classes.add(label)
+        
+        color = get_color(label)
+        cv2.rectangle(img, (x1, y1), (x2, y2), color, 2)
+        text = f"{label} {conf:.2f}"
+        cv2.putText(img, text, (x1, max(y1 - 10, 0)), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+        detections.append(f"{label}: {conf:.2f}")
+    
+    # Compliance check
+    if "hardhat" in detected_classes:
+        compliance["hardhat"] = "✅ COMPLIANT"
+    if "no-hardhat" in detected_classes:
+        compliance["hardhat"] = "❌ VIOLATION"
+    if "mask" in detected_classes:
+        compliance["mask"] = "✅ COMPLIANT"
+    if "no-mask" in detected_classes:
+        compliance["mask"] = "❌ VIOLATION"
+    if "safety vest" in detected_classes:
+        compliance["safety_vest"] = "✅ COMPLIANT"
+    if "no-safety vest" in detected_classes:
+        compliance["safety_vest"] = "❌ VIOLATION"
+    
+    # Convert back to RGB
+    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    output_image = Image.fromarray(img_rgb)
+    
+    report = f"""### PPE Compliance Report
+- **Hard Hat**: {compliance['hardhat']}
+- **Mask**: {compliance['mask']}
+- **Safety Vest**: {compliance['safety_vest']}
+
+### Detections ({len(detections)} objects)
+{chr(10).join(['- ' + d for d in detections]) if detections else 'No objects detected'}
+"""
+    return output_image, report
+
+with gr.Blocks(title="PPE Compliance Detection") as demo:
+    gr.Markdown("# 🦺 PPE Compliance Detection for Construction Sites")
+    gr.Markdown("Upload a construction site image to detect Personal Protective Equipment (PPE) compliance.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(type="pil", label="Upload Image")
+            conf_slider = gr.Slider(0.1, 0.9, value=0.25, step=0.05, label="Confidence Threshold")
+            detect_btn = gr.Button("Detect PPE", variant="primary")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Detected Objects")
+            output_text = gr.Markdown(label="Compliance Report")
+    
+    detect_btn.click(fn=detect_ppe, inputs=[input_image, conf_slider], outputs=[output_image, output_text])
+    
+    gr.Markdown("""
+    ## Classes Detected
+    - ✅ **Compliant PPE**: hardhat, mask, safety vest, gloves, safety shoes
+    - ❌ **Violations**: no-hardhat, no-mask, no-safety vest
+    - 🔵 **Other**: person, equipment, vehicles, barricades
+    """)
+
+if __name__ == "__main__":
+    demo.launch()