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detector/__init__.py

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+from .gesture_detector import detect_gesture

detector/gesture_detector.py

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+from ultralytics import YOLO
+from PIL import Image
+import cv2
+import os
+from datetime import datetime
+import base64
+
+# Load model YOLO hanya sekali
+model = YOLO("best (2).pt")
+
+# Buat folder hasil
+os.makedirs("detected_images", exist_ok=True)
+
+def detect_gesture(image_file):
+    image = Image.open(image_file.stream).convert("RGB")
+    results = model.predict(image, conf=0.3)
+
+    detections = []
+    if results[0].boxes is not None:
+        for box in results[0].boxes:
+            class_id = int(box.cls[0])
+            confidence = float(box.conf[0])
+            label = model.names[class_id]
+            x1, y1, x2, y2 = box.xyxy[0].tolist()
+
+            detections.append({
+                "label": label,
+                "confidence": round(confidence, 2),
+                "bbox": {
+                    "x1": round(x1, 2),
+                    "y1": round(y1, 2),
+                    "x2": round(x2, 2),
+                    "y2": round(y2, 2)
+                }
+            })
+
+    img_with_boxes = results[0].plot()
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    saved_filename = f"detected_images/detection_{timestamp}.jpg"
+    cv2.imwrite(saved_filename, img_with_boxes)
+
+    _, buffer = cv2.imencode(".jpg", img_with_boxes)
+    img_base64 = base64.b64encode(buffer).decode("utf-8")
+
+    return {
+        "saved_to": saved_filename,
+        "image_base64": img_base64,
+        "detections": detections,
+        "total_detections": len(detections)
+    }